First change the directory of your working folder to the data that you have collated of DC motor. You can do
directly from a icon given on the top. After that collect whole data into your matlab program in the form of cell
array for which code is given below.
filenames = 'DATA*'
filenames = 'DATA*'
files=[pwd '/' filenames '.xlsx']
files = '/home/bhoomik/Desktop/Matlab /Data/DATA*.xlsx'
ds=datastore(files)
ds =
SpreadsheetDatastore with properties: Files: { '/home/bhoomik/Desktop/Matlab /Data/DATA1.xlsx'; '/home/bhoomik/Desktop/Matlab /Data/DATA10.xlsx'; '/home/bhoomik/Desktop/Matlab /Data/DATA11.xlsx' ... and 40 more } Folders: { '/home/bhoomik/Desktop/Matlab /Data' } AlternateFileSystemRoots: {} Sheets: '' Range: '' Sheet Format Properties: NumHeaderLines: 0 VariableNamingRule: 'modify' ReadVariableNames: true VariableNames: {'ID', 't', 'Ia' ... and 3 more} VariableTypes: {'double', 'double', 'double' ... and 3 more} Properties that control the table returned by preview, read, readall: SelectedVariableNames: {'ID', 't', 'Ia' ... and 3 more} SelectedVariableTypes: {'double', 'double', 'double' ... and 3 more} ReadSize: 'file' OutputType: 'table' RowTimes: [] Write-specific Properties: SupportedOutputFormats: ["txt" "csv" "xlsx" "xls" "parquet" "parq"] DefaultOutputFormat: "xlsx"
Data is column Table(43x1 array) in which 43 Dataset is stored in this Data Table
Data=cell(43,1)
Data = 43×1 cell
 1
1[ ]
2[ ]
3[ ]
4[ ]
5[ ]
6[ ]
7[ ]
8[ ]
9[ ]
10[ ]
11[ ]
12[ ]
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
fensemble=fileEnsembleDatastore(pwd,'.xlsx');
new_filenames=fensemble.Files
new_filenames = 43×1 string
"/home/bhoomik/Desktop/Matla…
"/home/bhoomik/Desktop/Matla…
"/home/bhoomik/Desktop/Matla…
"/home/bhoomik/Desktop/Matla…
"/home/bhoomik/Desktop/Matla…
"/home/bhoomik/Desktop/Matla…
"/home/bhoomik/Desktop/Matla…
"/home/bhoomik/Desktop/Matla…
"/home/bhoomik/Desktop/Matla…
"/home/bhoomik/Desktop/Matla…
reset(ds)
for i=1:numel(new_filenames)
t=read(ds)
Data{i}=t
end
t = 256×6 table
 IDtIaIfNT
11092.98721.06659.549399.1687
210.000092.98711.06659.690398.2505
310.000092.98691.06659.829997.4927
410.000092.98671.06659.968396.8706
510.000092.98641.066510.251695.8754
610.000092.98601.066510.532095.2143
710.000092.98571.066510.810594.7877
810.000092.98531.066511.087594.5158
910.000192.98461.066511.613494.2601
1010.000192.98391.066512.138094.1496
1110.000192.98311.066512.662194.0893
1210.000192.98231.066513.186194.0560
1310.000192.98151.066513.709894.0414
1410.000292.97851.066515.398294.0255
1510.000292.97531.066517.086394.0286
1610.000392.97171.066518.774394.0274
1710.000392.96791.066520.462394.0228
1810.000892.91981.066533.772693.9735
1910.001292.85321.066547.070493.9062
2010.001692.76861.066560.352593.8206
2110.003192.36301.0665105.816093.4104
2210.004591.78141.0665150.961092.8223
2310.006091.04301.0665195.683692.0754
2410.007490.16831.0665239.889891.1908
2510.011587.10551.0665361.735688.0933
2610.015683.46431.0665477.492784.4108
2710.019779.52251.0665586.329280.4243
2810.023975.46991.0665687.886776.3258
2910.028071.43451.0665782.113072.2446
3010.034765.04521.0665921.409665.7829
3110.041559.16331.06651.0425e+0359.8342
3210.048253.89051.06651.1469e+0354.5016
3310.055049.23781.06651.2367e+0349.7962
3410.061745.17421.06651.3135e+0345.6865
3510.073939.15281.06651.4251e+0339.5968
3610.086234.59351.06651.5084e+0334.9858
3710.098431.17511.06651.5704e+0331.5286
3810.110628.61741.06651.6167e+0328.9419
3910.122826.70501.06651.6511e+0327.0078
4010.141824.66761.06651.6876e+0324.9473
4110.160923.38631.06651.7106e+0323.6515
4210.179922.57311.06651.7253e+0322.8291
4310.198922.05291.06651.7346e+0322.3030
4410.217921.72181.06651.7404e+0321.9682
4510.248121.44221.06651.7453e+0321.6853
4610.278321.31261.06651.7477e+0321.5543
4710.308421.24441.06651.7490e+0321.4853
4810.338621.20471.06651.7497e+0321.4452
4910.368821.18451.06651.7500e+0321.4248
5010.456821.16801.06651.7502e+0321.4080
5110.544821.17541.06651.7500e+0321.4156
5210.632821.18091.06651.7499e+0321.4211
5310.720821.18041.06651.7500e+0321.4206
5411.165121.17731.06651.7500e+0321.4174
5511.609521.17701.06651.7500e+0321.4171
5612.053821.17711.06651.7500e+0321.4172
5713.053821.17711.06651.7500e+0321.4173
5814.053821.17711.06651.7500e+0321.4173
5915.053821.17711.06651.7500e+0321.4173
6016.000021.17711.06651.7500e+0321.4173
6116.000021.17711.06651.7500e+0321.4173
6216.000021.17711.06651.7500e+0321.4173
6317.000021.18241.06651.7518e+0321.4226
6418.000021.18291.06651.7537e+0321.4231
6519.000021.18321.06651.7556e+0321.4234
66110.000021.18371.06651.7574e+0321.4239
67111.000021.18431.06651.7593e+0321.4245
68112.000021.18481.06651.7612e+0321.4251
69113.000021.18541.06651.7631e+0321.4257
70114.000021.18601.06651.7649e+0321.4262
71115.000021.18661.06651.7668e+0321.4268
72116.000021.18711.06651.7687e+0321.4274
73117.000021.18771.06651.7706e+0321.4280
74118.000021.18831.06651.7724e+0321.4285
75119.000021.18881.06651.7743e+0321.4291
76120.000021.18941.06651.7762e+0321.4297
77121.000021.19001.06651.7781e+0321.4303
78122.000021.19061.06651.7799e+0321.4309
79123.000021.19111.06651.7818e+0321.4314
80124.000021.19171.06651.7837e+0321.4320
81125.000021.19231.06651.7855e+0321.4326
82126.000021.19291.06651.7874e+0321.4332
83127.000021.19341.06651.7893e+0321.4338
84128.000021.19401.06651.7912e+0321.4343
85129.000021.19461.06651.7930e+0321.4349
86130.000021.19511.06651.7949e+0321.4355
87131.000021.19571.06651.7968e+0321.4361
88132.000021.19631.06651.7987e+0321.4367
89133.000021.19691.06651.8005e+0321.4372
90134.000021.19741.06651.8024e+0321.4378
91135.000021.19801.06651.8043e+0321.4384
92136.000021.19861.06651.8062e+0321.4390
93137.000021.19921.06651.8080e+0321.4396
94138.000021.19971.06651.8099e+0321.4401
95139.000021.20031.06651.8118e+0321.4407
96140.000021.20091.06651.8137e+0321.4413
97141.000021.20151.06651.8155e+0321.4419
98142.000021.20201.06651.8174e+0321.4425
99143.000021.20261.06651.8193e+0321.4430
100144.000021.20321.06651.8212e+0321.4436
⋮
Data = 43×1 cell
 1
1256×6 table
2[ ]
3[ ]
4[ ]
5[ ]
6[ ]
7[ ]
8[ ]
9[ ]
10[ ]
11[ ]
12[ ]
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 236×6 table
 IDtIaIfNT
110092.98721.06659.549399.1687
2100.000092.98711.06659.690398.2505
3100.000092.98691.06659.829997.4927
4100.000092.98671.06659.968396.8706
5100.000092.98641.066510.251695.8754
6100.000092.98601.066510.532095.2143
7100.000092.98571.066510.810594.7877
8100.000092.98531.066511.087594.5158
9100.000192.98461.066511.613494.2601
10100.000192.98391.066512.138094.1496
11100.000192.98311.066512.662194.0893
12100.000192.98231.066513.186194.0560
13100.000192.98151.066513.709894.0414
14100.000292.97851.066515.398294.0255
15100.000292.97531.066517.086394.0286
16100.000392.97171.066518.774394.0274
17100.000392.96791.066520.462394.0228
18100.000892.91981.066533.772693.9735
19100.001292.85321.066547.070493.9062
20100.001692.76861.066560.352593.8206
21100.003192.36301.0665105.816093.4104
22100.004591.78141.0665150.961092.8223
23100.006091.04301.0665195.683692.0754
24100.007490.16831.0665239.889891.1908
25100.011587.10551.0665361.735688.0933
26100.015683.46431.0665477.492784.4108
27100.019779.52251.0665586.329280.4243
28100.023975.46991.0665687.886776.3258
29100.028071.43451.0665782.113072.2446
30100.034765.04521.0665921.409665.7829
31100.041559.16331.06651.0425e+0359.8342
32100.048253.89051.06651.1469e+0354.5016
33100.055049.23781.06651.2367e+0349.7962
34100.061745.17421.06651.3135e+0345.6865
35100.073939.15281.06651.4251e+0339.5968
36100.086234.59351.06651.5084e+0334.9858
37100.098431.17511.06651.5704e+0331.5286
38100.110628.61741.06651.6167e+0328.9419
39100.122826.70501.06651.6511e+0327.0078
40100.141824.66761.06651.6876e+0324.9473
41100.160923.38631.06651.7106e+0323.6515
42100.179922.57311.06651.7253e+0322.8291
43100.198922.05291.06651.7346e+0322.3030
44100.217921.72181.06651.7404e+0321.9682
45100.248121.44221.06651.7453e+0321.6853
46100.278321.31261.06651.7477e+0321.5543
47100.308421.24441.06651.7490e+0321.4853
48100.338621.20471.06651.7497e+0321.4452
49100.368821.18451.06651.7500e+0321.4248
50100.456821.16801.06651.7502e+0321.4080
51100.544821.17541.06651.7500e+0321.4156
52100.632821.18091.06651.7499e+0321.4211
53100.720821.18041.06651.7500e+0321.4206
54101.165121.17731.06651.7500e+0321.4174
55101.609521.17701.06651.7500e+0321.4171
56102.053821.17711.06651.7500e+0321.4172
57103.053821.17711.06651.7500e+0321.4173
58104.053821.17711.06651.7500e+0321.4173
59105.053821.17711.06651.7500e+0321.4173
60106.053821.17711.06651.7500e+0321.4173
61107.053821.17711.06651.7500e+0321.4173
62108.053821.17711.06651.7500e+0321.4173
63109.053821.17711.06651.7500e+0321.4173
641010.000021.17711.06651.7500e+0321.4173
651010.000021.17711.06651.7500e+0321.4173
661010.000021.17711.06651.7500e+0321.4173
671011.000021.18901.06651.7540e+0321.4293
681012.000021.19001.06651.7582e+0321.4303
691013.000021.19071.06651.7625e+0321.4310
701014.000021.19191.06651.7667e+0321.4322
711015.000021.19321.06651.7709e+0321.4335
721016.000021.19451.06651.7751e+0321.4348
731017.000021.19581.06651.7793e+0321.4361
741018.000021.19701.06651.7835e+0321.4374
751019.000021.19831.06651.7878e+0321.4387
761020.000021.19961.06651.7920e+0321.4400
771021.000021.20091.06651.7962e+0321.4413
781022.000021.20221.06651.8004e+0321.4426
791023.000021.20351.06651.8046e+0321.4439
801024.000021.20481.06651.8089e+0321.4452
811025.000021.20611.06651.8131e+0321.4466
821026.000021.20741.06651.8173e+0321.4479
831027.000021.20861.06651.8215e+0321.4492
841028.000021.20991.06651.8257e+0321.4505
851029.000021.21121.06651.8299e+0321.4518
861030.000021.21251.06651.8342e+0321.4531
871031.000021.21381.06651.8384e+0321.4544
881032.000021.21511.06651.8426e+0321.4557
891033.000021.21641.06651.8468e+0321.4570
901034.000021.21771.06651.8510e+0321.4583
911035.000021.21901.06651.8552e+0321.4596
921036.000021.22031.06651.8595e+0321.4609
931037.000021.22151.06651.8637e+0321.4622
941038.000021.22281.06651.8679e+0321.4635
951039.000021.22411.06651.8721e+0321.4648
961040.000021.22541.06651.8763e+0321.4661
971041.000021.22671.06651.8805e+0321.4674
981042.000021.22801.06651.8848e+0321.4687
991043.000021.22931.06651.8890e+0321.4700
1001044.000021.23061.06651.8932e+0321.4713
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3[ ]
4[ ]
5[ ]
6[ ]
7[ ]
8[ ]
9[ ]
10[ ]
11[ ]
12[ ]
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 226×6 table
 IDtIaIfNT
111092.98721.06659.549399.1687
2110.000092.98711.06659.690398.2505
3110.000092.98691.06659.829997.4927
4110.000092.98671.06659.968396.8706
5110.000092.98641.066510.251695.8754
6110.000092.98601.066510.532095.2143
7110.000092.98571.066510.810594.7877
8110.000092.98531.066511.087594.5158
9110.000192.98461.066511.613494.2601
10110.000192.98391.066512.138094.1496
11110.000192.98311.066512.662194.0893
12110.000192.98231.066513.186194.0560
13110.000192.98151.066513.709894.0414
14110.000292.97851.066515.398294.0255
15110.000292.97531.066517.086394.0286
16110.000392.97171.066518.774394.0274
17110.000392.96791.066520.462394.0228
18110.000892.91981.066533.772693.9735
19110.001292.85321.066547.070493.9062
20110.001692.76861.066560.352593.8206
21110.003192.36301.0665105.816093.4104
22110.004591.78141.0665150.961092.8223
23110.006091.04301.0665195.683692.0754
24110.007490.16831.0665239.889891.1908
25110.011587.10551.0665361.735688.0933
26110.015683.46431.0665477.492784.4108
27110.019779.52251.0665586.329280.4243
28110.023975.46991.0665687.886776.3258
29110.028071.43451.0665782.113072.2446
30110.034765.04521.0665921.409665.7829
31110.041559.16331.06651.0425e+0359.8342
32110.048253.89051.06651.1469e+0354.5016
33110.055049.23781.06651.2367e+0349.7962
34110.061745.17421.06651.3135e+0345.6865
35110.073939.15281.06651.4251e+0339.5968
36110.086234.59351.06651.5084e+0334.9858
37110.098431.17511.06651.5704e+0331.5286
38110.110628.61741.06651.6167e+0328.9419
39110.122826.70501.06651.6511e+0327.0078
40110.141824.66761.06651.6876e+0324.9473
41110.160923.38631.06651.7106e+0323.6515
42110.179922.57311.06651.7253e+0322.8291
43110.198922.05291.06651.7346e+0322.3030
44110.217921.72181.06651.7404e+0321.9682
45110.248121.44221.06651.7453e+0321.6853
46110.278321.31261.06651.7477e+0321.5543
47110.308421.24441.06651.7490e+0321.4853
48110.338621.20471.06651.7497e+0321.4452
49110.368821.18451.06651.7500e+0321.4248
50110.456821.16801.06651.7502e+0321.4080
51110.544821.17541.06651.7500e+0321.4156
52110.632821.18091.06651.7499e+0321.4211
53110.720821.18041.06651.7500e+0321.4206
54111.165121.17731.06651.7500e+0321.4174
55111.609521.17701.06651.7500e+0321.4171
56112.053821.17711.06651.7500e+0321.4172
57113.053821.17711.06651.7500e+0321.4173
58114.053821.17711.06651.7500e+0321.4173
59115.000021.17711.06651.7500e+0321.4173
60115.000021.17711.06651.7500e+0321.4173
61115.000021.17711.06651.7500e+0321.4173
62116.000021.19161.06651.7549e+0321.4320
63117.000021.19291.06651.7600e+0321.4332
64118.000021.19371.06651.7652e+0321.4340
65119.000021.19511.06651.7704e+0321.4355
661110.000021.19671.06651.7755e+0321.4371
671111.000021.19831.06651.7807e+0321.4387
681112.000021.19991.06651.7858e+0321.4403
691113.000021.20151.06651.7910e+0321.4419
701114.000021.20301.06651.7961e+0321.4435
711115.000021.20461.06651.8013e+0321.4451
721116.000021.20621.06651.8065e+0321.4467
731117.000021.20781.06651.8116e+0321.4483
741118.000021.20941.06651.8168e+0321.4499
751119.000021.21091.06651.8219e+0321.4515
761120.000021.21251.06651.8271e+0321.4531
771121.000021.21411.06651.8322e+0321.4547
781122.000021.21571.06651.8374e+0321.4562
791123.000021.21721.06651.8425e+0321.4578
801124.000021.21881.06651.8477e+0321.4594
811125.000021.22041.06651.8528e+0321.4610
821126.000021.22201.06651.8580e+0321.4626
831127.000021.22351.06651.8632e+0321.4642
841128.000021.22511.06651.8683e+0321.4658
851129.000021.22671.06651.8735e+0321.4674
861130.000021.22831.06651.8786e+0321.4690
871131.000021.22981.06651.8838e+0321.4706
881132.000021.23141.06651.8889e+0321.4722
891133.000021.23301.06651.8941e+0321.4738
901134.000021.23461.06651.8992e+0321.4754
911135.000021.23611.06651.9044e+0321.4770
921136.000021.23771.06651.9096e+0321.4786
931137.000021.23931.06651.9147e+0321.4802
941138.000021.24091.06651.9199e+0321.4817
951139.000021.24241.06651.9250e+0321.4833
961140.000021.24401.06651.9302e+0321.4849
971141.000021.24561.06651.9353e+0321.4865
981142.000021.24721.06651.9405e+0321.4881
991143.000021.24881.06651.9456e+0321.4897
1001144.000021.25031.06651.9508e+0321.4913
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4[ ]
5[ ]
6[ ]
7[ ]
8[ ]
9[ ]
10[ ]
11[ ]
12[ ]
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 246×6 table
 IDtIaIfNT
112092.98721.06659.549399.1687
2120.000092.98711.06659.690398.2505
3120.000092.98691.06659.829997.4927
4120.000092.98671.06659.968396.8706
5120.000092.98641.066510.251695.8754
6120.000092.98601.066510.532095.2143
7120.000092.98571.066510.810594.7877
8120.000092.98531.066511.087594.5158
9120.000192.98461.066511.613494.2601
10120.000192.98391.066512.138094.1496
11120.000192.98311.066512.662194.0893
12120.000192.98231.066513.186194.0560
13120.000192.98151.066513.709894.0414
14120.000292.97851.066515.398294.0255
15120.000292.97531.066517.086394.0286
16120.000392.97171.066518.774394.0274
17120.000392.96791.066520.462394.0228
18120.000892.91981.066533.772693.9735
19120.001292.85321.066547.070493.9062
20120.001692.76861.066560.352593.8206
21120.003192.36301.0665105.816093.4104
22120.004591.78141.0665150.961092.8223
23120.006091.04301.0665195.683692.0754
24120.007490.16831.0665239.889891.1908
25120.011587.10551.0665361.735688.0933
26120.015683.46431.0665477.492784.4108
27120.019779.52251.0665586.329280.4243
28120.023975.46991.0665687.886776.3258
29120.028071.43451.0665782.113072.2446
30120.034765.04521.0665921.409665.7829
31120.041559.16331.06651.0425e+0359.8342
32120.048253.89051.06651.1469e+0354.5016
33120.055049.23781.06651.2367e+0349.7962
34120.061745.17421.06651.3135e+0345.6865
35120.073939.15281.06651.4251e+0339.5968
36120.086234.59351.06651.5084e+0334.9858
37120.098431.17511.06651.5704e+0331.5286
38120.110628.61741.06651.6167e+0328.9419
39120.122826.70501.06651.6511e+0327.0078
40120.141824.66761.06651.6876e+0324.9473
41120.160923.38631.06651.7106e+0323.6515
42120.179922.57311.06651.7253e+0322.8291
43120.198922.05291.06651.7346e+0322.3030
44120.217921.72181.06651.7404e+0321.9682
45120.248121.44221.06651.7453e+0321.6853
46120.278321.31261.06651.7477e+0321.5543
47120.308421.24441.06651.7490e+0321.4853
48120.338621.20471.06651.7497e+0321.4452
49120.368821.18451.06651.7500e+0321.4248
50120.456821.16801.06651.7502e+0321.4080
51120.544821.17541.06651.7500e+0321.4156
52120.632821.18091.06651.7499e+0321.4211
53120.720821.18041.06651.7500e+0321.4206
54121.165121.17731.06651.7500e+0321.4174
55121.609521.17701.06651.7500e+0321.4171
56122.053821.17711.06651.7500e+0321.4172
57123.053821.17711.06651.7500e+0321.4173
58124.053821.17711.06651.7500e+0321.4173
59125.053821.17711.06651.7500e+0321.4173
60126.053821.17711.06651.7500e+0321.4173
61127.053821.17711.06651.7500e+0321.4173
62128.053821.17711.06651.7500e+0321.4173
63129.053821.17711.06651.7500e+0321.4173
641210.000021.17711.06651.7500e+0321.4173
651210.000021.17711.06651.7500e+0321.4173
661210.000021.17711.06651.7500e+0321.4173
671211.000021.19301.06651.7553e+0321.4333
681212.000021.19431.06651.7609e+0321.4347
691213.000021.19521.06651.7666e+0321.4356
701214.000021.19681.06651.7722e+0321.4371
711215.000021.19851.06651.7778e+0321.4389
721216.000021.20021.06651.7835e+0321.4407
731217.000021.20201.06651.7891e+0321.4424
741218.000021.20371.06651.7947e+0321.4441
751219.000021.20541.06651.8003e+0321.4459
761220.000021.20711.06651.8060e+0321.4476
771221.000021.20881.06651.8116e+0321.4494
781222.000021.21061.06651.8172e+0321.4511
791223.000021.21231.06651.8228e+0321.4528
801224.000021.21401.06651.8285e+0321.4546
811225.000021.21571.06651.8341e+0321.4563
821226.000021.21741.06651.8397e+0321.4580
831227.000021.21921.06651.8453e+0321.4598
841228.000021.22091.06651.8509e+0321.4615
851229.000021.22261.06651.8566e+0321.4633
861230.000021.22431.06651.8622e+0321.4650
871231.000021.22601.06651.8678e+0321.4667
881232.000021.22781.06651.8734e+0321.4685
891233.000021.22951.06651.8791e+0321.4702
901234.000021.23121.06651.8847e+0321.4720
911235.000021.23291.06651.8903e+0321.4737
921236.000021.23461.06651.8959e+0321.4754
931237.000021.23641.06651.9016e+0321.4772
941238.000021.23811.06651.9072e+0321.4789
951239.000021.23981.06651.9128e+0321.4807
961240.000021.24151.06651.9184e+0321.4824
971241.000021.24321.06651.9241e+0321.4841
981242.000021.24491.06651.9297e+0321.4859
991243.000021.24671.06651.9353e+0321.4876
1001244.000021.24841.06651.9409e+0321.4893
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5[ ]
6[ ]
7[ ]
8[ ]
9[ ]
10[ ]
11[ ]
12[ ]
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 222×6 table
 IDtIaIfNT
113092.98721.06659.549399.1687
2130.000092.98711.06659.690398.2505
3130.000092.98691.06659.829997.4927
4130.000092.98671.06659.968396.8706
5130.000092.98641.066510.251695.8754
6130.000092.98601.066510.532095.2143
7130.000092.98571.066510.810594.7877
8130.000092.98531.066511.087594.5158
9130.000192.98461.066511.613494.2601
10130.000192.98391.066512.138094.1496
11130.000192.98311.066512.662194.0893
12130.000192.98231.066513.186194.0560
13130.000192.98151.066513.709894.0414
14130.000292.97851.066515.398294.0255
15130.000292.97531.066517.086394.0286
16130.000392.97171.066518.774394.0274
17130.000392.96791.066520.462394.0228
18130.000892.91981.066533.772693.9735
19130.001292.85321.066547.070493.9062
20130.001692.76861.066560.352593.8206
21130.003192.36301.0665105.816093.4104
22130.004591.78141.0665150.961092.8223
23130.006091.04301.0665195.683692.0754
24130.007490.16831.0665239.889891.1908
25130.011587.10551.0665361.735688.0933
26130.015683.46431.0665477.492784.4108
27130.019779.52251.0665586.329280.4243
28130.023975.46991.0665687.886776.3258
29130.028071.43451.0665782.113072.2446
30130.034765.04521.0665921.409665.7829
31130.041559.16331.06651.0425e+0359.8342
32130.048253.89051.06651.1469e+0354.5016
33130.055049.23781.06651.2367e+0349.7962
34130.061745.17421.06651.3135e+0345.6865
35130.073939.15281.06651.4251e+0339.5968
36130.086234.59351.06651.5084e+0334.9858
37130.098431.17511.06651.5704e+0331.5286
38130.110628.61741.06651.6167e+0328.9419
39130.122826.70501.06651.6511e+0327.0078
40130.141824.66761.06651.6876e+0324.9473
41130.160923.38631.06651.7106e+0323.6515
42130.179922.57311.06651.7253e+0322.8291
43130.198922.05291.06651.7346e+0322.3030
44130.217921.72181.06651.7404e+0321.9682
45130.248121.44221.06651.7453e+0321.6853
46130.278321.31261.06651.7477e+0321.5543
47130.308421.24441.06651.7490e+0321.4853
48130.338621.20471.06651.7497e+0321.4452
49130.368821.18451.06651.7500e+0321.4248
50130.456821.16801.06651.7502e+0321.4080
51130.544821.17541.06651.7500e+0321.4156
52130.632821.18091.06651.7499e+0321.4211
53130.720821.18041.06651.7500e+0321.4206
54131.165121.17731.06651.7500e+0321.4174
55131.609521.17701.06651.7500e+0321.4171
56132.053821.17711.06651.7500e+0321.4172
57133.053821.17711.06651.7500e+0321.4173
58134.053821.17711.06651.7500e+0321.4173
59135.000021.17711.06651.7500e+0321.4173
60135.000021.17711.06651.7500e+0321.4173
61135.000021.17711.06651.7500e+0321.4173
62135.822421.19371.06651.7547e+0321.4341
63136.644821.19511.06651.7597e+0321.4354
64137.467221.19581.06651.7647e+0321.4361
65138.467221.19741.06651.7708e+0321.4378
66139.467221.19931.06651.7769e+0321.4397
671310.467221.20121.06651.7830e+0321.4416
681311.467221.20301.06651.7891e+0321.4435
691312.467221.20491.06651.7952e+0321.4454
701313.467221.20681.06651.8013e+0321.4473
711314.467221.20861.06651.8074e+0321.4491
721315.467221.21051.06651.8135e+0321.4510
731316.467221.21241.06651.8196e+0321.4529
741317.467221.21421.06651.8257e+0321.4548
751318.467221.21611.06651.8317e+0321.4567
761319.467221.21791.06651.8378e+0321.4586
771320.467221.21981.06651.8439e+0321.4604
781321.467221.22171.06651.8500e+0321.4623
791322.467221.22351.06651.8561e+0321.4642
801323.467221.22541.06651.8622e+0321.4661
811324.467221.22731.06651.8683e+0321.4680
821325.467221.22911.06651.8744e+0321.4699
831326.467221.23101.06651.8805e+0321.4717
841327.467221.23281.06651.8866e+0321.4736
851328.467221.23471.06651.8927e+0321.4755
861329.467221.23661.06651.8988e+0321.4774
871330.467221.23841.06651.9048e+0321.4793
881331.467221.24031.06651.9109e+0321.4812
891332.467221.24221.06651.9170e+0321.4830
901333.467221.24401.06651.9231e+0321.4849
911334.467221.24591.06651.9292e+0321.4868
921335.467221.24771.06651.9353e+0321.4887
931336.467221.24961.06651.9414e+0321.4906
941337.467221.25151.06651.9475e+0321.4925
951338.467221.25331.06651.9536e+0321.4944
961339.467221.25521.06651.9597e+0321.4962
971340.467221.25711.06651.9658e+0321.4981
981341.467221.25891.06651.9719e+0321.5000
991342.467221.26081.06651.9780e+0321.5019
1001343.467221.26261.06651.9840e+0321.5038
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6[ ]
7[ ]
8[ ]
9[ ]
10[ ]
11[ ]
12[ ]
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 207×6 table
 IDtIaIfNT
114092.98721.06659.549399.1687
2140.000092.98711.06659.690398.2505
3140.000092.98691.06659.829997.4927
4140.000092.98671.06659.968396.8706
5140.000092.98641.066510.251695.8754
6140.000092.98601.066510.532095.2143
7140.000092.98571.066510.810594.7877
8140.000092.98531.066511.087594.5158
9140.000192.98461.066511.613494.2601
10140.000192.98391.066512.138094.1496
11140.000192.98311.066512.662194.0893
12140.000192.98231.066513.186194.0560
13140.000192.98151.066513.709894.0414
14140.000292.97851.066515.398294.0255
15140.000292.97531.066517.086394.0286
16140.000392.97171.066518.774394.0274
17140.000392.96791.066520.462394.0228
18140.000892.91981.066533.772693.9735
19140.001292.85321.066547.070493.9062
20140.001692.76861.066560.352593.8206
21140.003192.36301.0665105.816093.4104
22140.004591.78141.0665150.961092.8223
23140.006091.04301.0665195.683692.0754
24140.007490.16831.0665239.889891.1908
25140.011587.10551.0665361.735688.0933
26140.015683.46431.0665477.492784.4108
27140.019779.52251.0665586.329280.4243
28140.023975.46991.0665687.886776.3258
29140.028071.43451.0665782.113072.2446
30140.034765.04521.0665921.409665.7829
31140.041559.16331.06651.0425e+0359.8342
32140.048253.89051.06651.1469e+0354.5016
33140.055049.23781.06651.2367e+0349.7962
34140.061745.17421.06651.3135e+0345.6865
35140.073939.15281.06651.4251e+0339.5968
36140.086234.59351.06651.5084e+0334.9858
37140.098431.17511.06651.5704e+0331.5286
38140.110628.61741.06651.6167e+0328.9419
39140.122826.70501.06651.6511e+0327.0078
40140.141824.66761.06651.6876e+0324.9473
41140.160923.38631.06651.7106e+0323.6515
42140.179922.57311.06651.7253e+0322.8291
43140.198922.05291.06651.7346e+0322.3030
44140.217921.72181.06651.7404e+0321.9682
45140.248121.44221.06651.7453e+0321.6853
46140.278321.31261.06651.7477e+0321.5543
47140.308421.24441.06651.7490e+0321.4853
48140.338621.20471.06651.7497e+0321.4452
49140.368821.18451.06651.7500e+0321.4248
50140.456821.16801.06651.7502e+0321.4080
51140.544821.17541.06651.7500e+0321.4156
52140.632821.18091.06651.7499e+0321.4211
53140.720821.18041.06651.7500e+0321.4206
54141.165121.17731.06651.7500e+0321.4174
55141.609521.17701.06651.7500e+0321.4171
56142.053821.17711.06651.7500e+0321.4172
57143.053821.17711.06651.7500e+0321.4173
58144.053821.17711.06651.7500e+0321.4173
59145.000021.17711.06651.7500e+0321.4173
60145.000021.17711.06651.7500e+0321.4173
61145.000021.17711.06651.7500e+0321.4173
62145.765621.19611.06651.7550e+0321.4365
63146.531221.19681.06651.7604e+0321.4372
64147.296921.19811.06651.7658e+0321.4385
65148.062521.19971.06651.7712e+0321.4401
66149.062521.20191.06651.7782e+0321.4423
671410.062521.20401.06651.7852e+0321.4445
681411.062521.20621.06651.7923e+0321.4466
691412.062521.20831.06651.7993e+0321.4488
701413.062521.21051.06651.8063e+0321.4510
711414.062521.21261.06651.8134e+0321.4532
721415.062521.21481.06651.8204e+0321.4553
731416.062521.21691.06651.8274e+0321.4575
741417.062521.21911.06651.8344e+0321.4597
751418.062521.22121.06651.8415e+0321.4619
761419.062521.22341.06651.8485e+0321.4640
771420.062521.22551.06651.8555e+0321.4662
781421.062521.22771.06651.8626e+0321.4684
791422.062521.22981.06651.8696e+0321.4706
801423.062521.23191.06651.8766e+0321.4727
811424.062521.23411.06651.8836e+0321.4749
821425.062521.23621.06651.8907e+0321.4771
831426.062521.23841.06651.8977e+0321.4792
841427.062521.24051.06651.9047e+0321.4814
851428.062521.24271.06651.9118e+0321.4836
861429.062521.24481.06651.9188e+0321.4858
871430.062521.24701.06651.9258e+0321.4879
881431.062521.24911.06651.9328e+0321.4901
891432.062521.25131.06651.9399e+0321.4923
901433.062521.25341.06651.9469e+0321.4945
911434.062521.25561.06651.9539e+0321.4966
921435.062521.25771.06651.9610e+0321.4988
931436.062521.25991.06651.9680e+0321.5010
941437.062521.26201.06651.9750e+0321.5032
951438.062521.26421.06651.9821e+0321.5053
961439.062521.26631.06651.9891e+0321.5075
971440.062521.26851.06651.9961e+0321.5097
981441.062521.27061.06652.0031e+0321.5119
991442.062521.27281.06652.0102e+0321.5140
1001443.062521.27491.06652.0172e+0321.5162
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7[ ]
8[ ]
9[ ]
10[ ]
11[ ]
12[ ]
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 177×6 table
 IDtIaIfNT
115092.98721.06659.549399.1687
2150.000092.98711.06659.690398.2505
3150.000092.98691.06659.829997.4927
4150.000092.98671.06659.968396.8706
5150.000092.98641.066510.251695.8754
6150.000092.98601.066510.532095.2143
7150.000092.98571.066510.810594.7877
8150.000092.98531.066511.087594.5158
9150.000192.98461.066511.613494.2601
10150.000192.98391.066512.138094.1496
11150.000192.98311.066512.662194.0893
12150.000192.98231.066513.186194.0560
13150.000192.98151.066513.709894.0414
14150.000292.97851.066515.398294.0255
15150.000292.97531.066517.086394.0286
16150.000392.97171.066518.774394.0274
17150.000392.96791.066520.462394.0228
18150.000892.91981.066533.772693.9735
19150.001292.85321.066547.070493.9062
20150.001692.76861.066560.352593.8206
21150.003192.36301.0665105.816093.4104
22150.004591.78141.0665150.961092.8223
23150.006091.04301.0665195.683692.0754
24150.007490.16831.0665239.889891.1908
25150.011587.10551.0665361.735688.0933
26150.015683.46431.0665477.492784.4108
27150.019779.52251.0665586.329280.4243
28150.023975.46991.0665687.886776.3258
29150.028071.43451.0665782.113072.2446
30150.034765.04521.0665921.409665.7829
31150.041559.16331.06651.0425e+0359.8342
32150.048253.89051.06651.1469e+0354.5016
33150.055049.23781.06651.2367e+0349.7962
34150.061745.17421.06651.3135e+0345.6865
35150.073939.15281.06651.4251e+0339.5968
36150.086234.59351.06651.5084e+0334.9858
37150.098431.17511.06651.5704e+0331.5286
38150.110628.61741.06651.6167e+0328.9419
39150.122826.70501.06651.6511e+0327.0078
40150.141824.66761.06651.6876e+0324.9473
41150.160923.38631.06651.7106e+0323.6515
42150.179922.57311.06651.7253e+0322.8291
43150.198922.05291.06651.7346e+0322.3030
44150.217921.72181.06651.7404e+0321.9682
45150.248121.44221.06651.7453e+0321.6853
46150.278321.31261.06651.7477e+0321.5543
47150.308421.24441.06651.7490e+0321.4853
48150.338621.20471.06651.7497e+0321.4452
49150.368821.18451.06651.7500e+0321.4248
50150.456821.16801.06651.7502e+0321.4080
51150.544821.17541.06651.7500e+0321.4156
52150.632821.18091.06651.7499e+0321.4211
53150.720821.18041.06651.7500e+0321.4206
54151.165121.17731.06651.7500e+0321.4174
55151.609521.17701.06651.7500e+0321.4171
56152.053821.17711.06651.7500e+0321.4172
57153.053821.17711.06651.7500e+0321.4173
58154.053821.17711.06651.7500e+0321.4173
59155.053821.17711.06651.7500e+0321.4173
60156.053821.17711.06651.7500e+0321.4173
61157.053821.17711.06651.7500e+0321.4173
62158.053821.17711.06651.7500e+0321.4173
63159.053821.17711.06651.7500e+0321.4173
641510.053821.17711.06651.7500e+0321.4173
651511.053821.17711.06651.7500e+0321.4173
661512.053821.17711.06651.7500e+0321.4173
671513.053821.17711.06651.7500e+0321.4173
681514.053821.17711.06651.7500e+0321.4173
691515.000021.17711.06651.7500e+0321.4173
701515.000021.17711.06651.7500e+0321.4173
711515.000021.17711.06651.7500e+0321.4173
721515.680221.20071.06651.7555e+0321.4411
731516.360521.20261.06651.7616e+0321.4430
741517.040721.20321.06651.7677e+0321.4437
751518.040721.20571.06651.7766e+0321.4461
761519.040721.20841.06651.7855e+0321.4489
771520.040721.21111.06651.7944e+0321.4517
781521.040721.21381.06651.8033e+0321.4544
791522.040721.21661.06651.8122e+0321.4572
801523.040721.21931.06651.8211e+0321.4599
811524.040721.22201.06651.8300e+0321.4627
821525.040721.22471.06651.8389e+0321.4654
831526.040721.22751.06651.8478e+0321.4682
841527.040721.23021.06651.8568e+0321.4709
851528.040721.23291.06651.8657e+0321.4737
861529.040721.23561.06651.8746e+0321.4764
871530.040721.23831.06651.8835e+0321.4792
881531.040721.24111.06651.8924e+0321.4819
891532.040721.24381.06651.9013e+0321.4847
901533.040721.24651.06651.9102e+0321.4875
911534.040721.24921.06651.9191e+0321.4902
921535.040721.25201.06651.9280e+0321.4930
931536.040721.25471.06651.9369e+0321.4957
941537.040721.25741.06651.9458e+0321.4985
951538.040721.26011.06651.9547e+0321.5012
961539.040721.26281.06651.9636e+0321.5040
971540.040721.26561.06651.9725e+0321.5067
981541.040721.26831.06651.9814e+0321.5095
991542.040721.27101.06651.9903e+0321.5122
1001543.040721.27371.06651.9992e+0321.5150
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8[ ]
9[ ]
10[ ]
11[ ]
12[ ]
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 276×6 table
 IDtIaIfNT
116092.98721.06659.549399.1687
2160.000092.98711.06659.690398.2505
3160.000092.98691.06659.829997.4927
4160.000092.98671.06659.968396.8706
5160.000092.98641.066510.251695.8754
6160.000092.98601.066510.532095.2143
7160.000092.98571.066510.810594.7877
8160.000092.98531.066511.087594.5158
9160.000192.98461.066511.613494.2601
10160.000192.98391.066512.138094.1496
11160.000192.98311.066512.662194.0893
12160.000192.98231.066513.186194.0560
13160.000192.98151.066513.709894.0414
14160.000292.97851.066515.398294.0255
15160.000292.97531.066517.086394.0286
16160.000392.97171.066518.774394.0274
17160.000392.96791.066520.462394.0228
18160.000892.91981.066533.772693.9735
19160.001292.85321.066547.070493.9062
20160.001692.76861.066560.352593.8206
21160.003192.36301.0665105.816093.4104
22160.004591.78141.0665150.961092.8223
23160.006091.04301.0665195.683692.0754
24160.007490.16831.0665239.889891.1908
25160.011587.10551.0665361.735688.0933
26160.015683.46431.0665477.492784.4108
27160.019779.52251.0665586.329280.4243
28160.023975.46991.0665687.886776.3258
29160.028071.43451.0665782.113072.2446
30160.034765.04521.0665921.409665.7829
31160.041559.16331.06651.0425e+0359.8342
32160.048253.89051.06651.1469e+0354.5016
33160.055049.23781.06651.2367e+0349.7962
34160.061745.17421.06651.3135e+0345.6865
35160.073939.15281.06651.4251e+0339.5968
36160.086234.59351.06651.5084e+0334.9858
37160.098431.17511.06651.5704e+0331.5286
38160.110628.61741.06651.6167e+0328.9419
39160.122826.70501.06651.6511e+0327.0078
40160.141824.66761.06651.6876e+0324.9473
41160.160923.38631.06651.7106e+0323.6515
42160.179922.57311.06651.7253e+0322.8291
43160.198922.05291.06651.7346e+0322.3030
44160.217921.72181.06651.7404e+0321.9682
45160.248121.44221.06651.7453e+0321.6853
46160.278321.31261.06651.7477e+0321.5543
47160.308421.24441.06651.7490e+0321.4853
48160.338621.20471.06651.7497e+0321.4452
49160.368821.18451.06651.7500e+0321.4248
50160.456821.16801.06651.7502e+0321.4080
51160.544821.17541.06651.7500e+0321.4156
52160.632821.18091.06651.7499e+0321.4211
53160.720821.18041.06651.7500e+0321.4206
54161.165121.17731.06651.7500e+0321.4174
55161.609521.17701.06651.7500e+0321.4171
56162.053821.17711.06651.7500e+0321.4172
57163.053821.17711.06651.7500e+0321.4173
58164.053821.17711.06651.7500e+0321.4173
59165.053821.17711.06651.7500e+0321.4173
60166.053821.17711.06651.7500e+0321.4173
61167.053821.17711.06651.7500e+0321.4173
62168.053821.17711.06651.7500e+0321.4173
63169.053821.17711.06651.7500e+0321.4173
641610.000021.17711.06651.7500e+0321.4173
651610.000021.17711.06651.7500e+0321.4173
661610.000021.17711.06651.7500e+0321.4173
671611.000021.16721.06691.7496e+0321.4159
681612.000021.15411.06751.7489e+0321.4152
691613.000021.14011.06821.7481e+0321.4148
701614.000021.12591.06891.7473e+0321.4145
711615.000021.11161.06961.7465e+0321.4143
721616.000021.09731.07031.7456e+0321.4140
731617.000021.08311.07111.7448e+0321.4138
741618.000021.06881.07181.7440e+0321.4135
751619.000021.05461.07251.7432e+0321.4133
761620.000021.04041.07321.7424e+0321.4130
771621.000021.02631.07391.7416e+0321.4128
781622.000021.01211.07461.7408e+0321.4125
791623.000020.99801.07531.7400e+0321.4123
801624.000020.98391.07601.7392e+0321.4120
811625.000020.96981.07671.7384e+0321.4118
821626.000020.95571.07751.7375e+0321.4115
831627.000020.94161.07821.7367e+0321.4113
841628.000020.92761.07891.7359e+0321.4110
851629.000020.91351.07961.7351e+0321.4108
861630.000020.89951.08031.7343e+0321.4106
871631.000020.88561.08101.7335e+0321.4103
881632.000020.87161.08171.7327e+0321.4101
891633.000020.85761.08241.7319e+0321.4098
901634.000020.84371.08311.7311e+0321.4096
911635.000020.82981.08391.7303e+0321.4093
921636.000020.81591.08461.7295e+0321.4091
931637.000020.80201.08531.7287e+0321.4088
941638.000020.78821.08601.7279e+0321.4086
951639.000020.77431.08671.7271e+0321.4083
961640.000020.76051.08741.7263e+0321.4081
971641.000020.74671.08811.7255e+0321.4078
981642.000020.73291.08881.7247e+0321.4076
991643.000020.71911.08951.7239e+0321.4074
1001644.000020.70541.09031.7231e+0321.4071
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9[ ]
10[ ]
11[ ]
12[ ]
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 271×6 table
 IDtIaIfNT
117092.98721.06659.549399.1687
2170.000092.98711.06659.690398.2505
3170.000092.98691.06659.829997.4927
4170.000092.98671.06659.968396.8706
5170.000092.98641.066510.251695.8754
6170.000092.98601.066510.532095.2143
7170.000092.98571.066510.810594.7877
8170.000092.98531.066511.087594.5158
9170.000192.98461.066511.613494.2601
10170.000192.98391.066512.138094.1496
11170.000192.98311.066512.662194.0893
12170.000192.98231.066513.186194.0560
13170.000192.98151.066513.709894.0414
14170.000292.97851.066515.398294.0255
15170.000292.97531.066517.086394.0286
16170.000392.97171.066518.774394.0274
17170.000392.96791.066520.462394.0228
18170.000892.91981.066533.772693.9735
19170.001292.85321.066547.070493.9062
20170.001692.76861.066560.352593.8206
21170.003192.36301.0665105.816093.4104
22170.004591.78141.0665150.961092.8223
23170.006091.04301.0665195.683692.0754
24170.007490.16831.0665239.889891.1908
25170.011587.10551.0665361.735688.0933
26170.015683.46431.0665477.492784.4108
27170.019779.52251.0665586.329280.4243
28170.023975.46991.0665687.886776.3258
29170.028071.43451.0665782.113072.2446
30170.034765.04521.0665921.409665.7829
31170.041559.16331.06651.0425e+0359.8342
32170.048253.89051.06651.1469e+0354.5016
33170.055049.23781.06651.2367e+0349.7962
34170.061745.17421.06651.3135e+0345.6865
35170.073939.15281.06651.4251e+0339.5968
36170.086234.59351.06651.5084e+0334.9858
37170.098431.17511.06651.5704e+0331.5286
38170.110628.61741.06651.6167e+0328.9419
39170.122826.70501.06651.6511e+0327.0078
40170.141824.66761.06651.6876e+0324.9473
41170.160923.38631.06651.7106e+0323.6515
42170.179922.57311.06651.7253e+0322.8291
43170.198922.05291.06651.7346e+0322.3030
44170.217921.72181.06651.7404e+0321.9682
45170.248121.44221.06651.7453e+0321.6853
46170.278321.31261.06651.7477e+0321.5543
47170.308421.24441.06651.7490e+0321.4853
48170.338621.20471.06651.7497e+0321.4452
49170.368821.18451.06651.7500e+0321.4248
50170.456821.16801.06651.7502e+0321.4080
51170.544821.17541.06651.7500e+0321.4156
52170.632821.18091.06651.7499e+0321.4211
53170.720821.18041.06651.7500e+0321.4206
54171.165121.17731.06651.7500e+0321.4174
55171.609521.17701.06651.7500e+0321.4171
56172.053821.17711.06651.7500e+0321.4172
57173.053821.17711.06651.7500e+0321.4173
58174.053821.17711.06651.7500e+0321.4173
59175.053821.17711.06651.7500e+0321.4173
60176.053821.17711.06651.7500e+0321.4173
61177.053821.17711.06651.7500e+0321.4173
62178.053821.17711.06651.7500e+0321.4173
63179.053821.17711.06651.7500e+0321.4173
641710.053821.17711.06651.7500e+0321.4173
651711.053821.17711.06651.7500e+0321.4173
661712.053821.17711.06651.7500e+0321.4173
671713.053821.17711.06651.7500e+0321.4173
681714.053821.17711.06651.7500e+0321.4173
691715.000021.17711.06651.7500e+0321.4173
701715.000021.17711.06651.7500e+0321.4173
711715.000021.17711.06651.7500e+0321.4173
721716.000021.16471.06701.7495e+0321.4155
731717.000021.14841.06781.7486e+0321.4146
741718.000021.13091.06871.7476e+0321.4142
751719.000021.11311.06951.7466e+0321.4139
761720.000021.09531.07041.7456e+0321.4135
771721.000021.07751.07131.7446e+0321.4132
781722.000021.05971.07221.7435e+0321.4129
791723.000021.04191.07311.7425e+0321.4126
801724.000021.02421.07401.7415e+0321.4123
811725.000021.00651.07491.7405e+0321.4120
821726.000020.98891.07581.7395e+0321.4117
831727.000020.97131.07661.7385e+0321.4114
841728.000020.95371.07751.7375e+0321.4111
851729.000020.93611.07841.7365e+0321.4107
861730.000020.91851.07931.7355e+0321.4104
871731.000020.90101.08021.7344e+0321.4101
881732.000020.88351.08111.7334e+0321.4098
891733.000020.86611.08201.7324e+0321.4095
901734.000020.84871.08291.7314e+0321.4092
911735.000020.83131.08381.7304e+0321.4089
921736.000020.81391.08461.7294e+0321.4086
931737.000020.79661.08551.7284e+0321.4083
941738.000020.77931.08641.7274e+0321.4080
951739.000020.76201.08731.7264e+0321.4077
961740.000020.74471.08821.7254e+0321.4074
971741.000020.72751.08911.7244e+0321.4070
981742.000020.71031.09001.7234e+0321.4067
991743.000020.69311.09091.7224e+0321.4064
1001744.000020.67601.09181.7214e+0321.4061
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10[ ]
11[ ]
12[ ]
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 281×6 table
 IDtIaIfNT
118092.98721.06659.549399.1687
2180.000092.98711.06659.690398.2505
3180.000092.98691.06659.829997.4927
4180.000092.98671.06659.968396.8706
5180.000092.98641.066510.251695.8754
6180.000092.98601.066510.532095.2143
7180.000092.98571.066510.810594.7877
8180.000092.98531.066511.087594.5158
9180.000192.98461.066511.613494.2601
10180.000192.98391.066512.138094.1496
11180.000192.98311.066512.662194.0893
12180.000192.98231.066513.186194.0560
13180.000192.98151.066513.709894.0414
14180.000292.97851.066515.398294.0255
15180.000292.97531.066517.086394.0286
16180.000392.97171.066518.774394.0274
17180.000392.96791.066520.462394.0228
18180.000892.91981.066533.772693.9735
19180.001292.85321.066547.070493.9062
20180.001692.76861.066560.352593.8206
21180.003192.36301.0665105.816093.4104
22180.004591.78141.0665150.961092.8223
23180.006091.04301.0665195.683692.0754
24180.007490.16831.0665239.889891.1908
25180.011587.10551.0665361.735688.0933
26180.015683.46431.0665477.492784.4108
27180.019779.52251.0665586.329280.4243
28180.023975.46991.0665687.886776.3258
29180.028071.43451.0665782.113072.2446
30180.034765.04521.0665921.409665.7829
31180.041559.16331.06651.0425e+0359.8342
32180.048253.89051.06651.1469e+0354.5016
33180.055049.23781.06651.2367e+0349.7962
34180.061745.17421.06651.3135e+0345.6865
35180.073939.15281.06651.4251e+0339.5968
36180.086234.59351.06651.5084e+0334.9858
37180.098431.17511.06651.5704e+0331.5286
38180.110628.61741.06651.6167e+0328.9419
39180.122826.70501.06651.6511e+0327.0078
40180.141824.66761.06651.6876e+0324.9473
41180.160923.38631.06651.7106e+0323.6515
42180.179922.57311.06651.7253e+0322.8291
43180.198922.05291.06651.7346e+0322.3030
44180.217921.72181.06651.7404e+0321.9682
45180.248121.44221.06651.7453e+0321.6853
46180.278321.31261.06651.7477e+0321.5543
47180.308421.24441.06651.7490e+0321.4853
48180.338621.20471.06651.7497e+0321.4452
49180.368821.18451.06651.7500e+0321.4248
50180.456821.16801.06651.7502e+0321.4080
51180.544821.17541.06651.7500e+0321.4156
52180.632821.18091.06651.7499e+0321.4211
53180.720821.18041.06651.7500e+0321.4206
54181.165121.17731.06651.7500e+0321.4174
55181.609521.17701.06651.7500e+0321.4171
56182.053821.17711.06651.7500e+0321.4172
57183.053821.17711.06651.7500e+0321.4173
58184.053821.17711.06651.7500e+0321.4173
59185.053821.17711.06651.7500e+0321.4173
60186.053821.17711.06651.7500e+0321.4173
61187.053821.17711.06651.7500e+0321.4173
62188.053821.17711.06651.7500e+0321.4173
63189.053821.17711.06651.7500e+0321.4173
641810.053821.17711.06651.7500e+0321.4173
651811.053821.17711.06651.7500e+0321.4173
661812.053821.17711.06651.7500e+0321.4173
671813.053821.17711.06651.7500e+0321.4173
681814.053821.17711.06651.7500e+0321.4173
691815.053821.17711.06651.7500e+0321.4173
701816.053821.17711.06651.7500e+0321.4173
711817.053821.17711.06651.7500e+0321.4173
721818.053821.17711.06651.7500e+0321.4173
731819.053821.17711.06651.7500e+0321.4173
741820.000021.17711.06651.7500e+0321.4173
751820.000021.17711.06651.7500e+0321.4173
761820.000021.17711.06651.7500e+0321.4173
771821.000021.16821.06691.7496e+0321.4160
781822.000021.15641.06741.7490e+0321.4154
791823.000021.14381.06801.7483e+0321.4151
801824.000021.13101.06871.7476e+0321.4148
811825.000021.11811.06931.7468e+0321.4146
821826.000021.10531.07001.7461e+0321.4144
831827.000021.09241.07061.7454e+0321.4141
841828.000021.07961.07121.7446e+0321.4139
851829.000021.06681.07191.7439e+0321.4137
861830.000021.05401.07251.7432e+0321.4135
871831.000021.04131.07321.7424e+0321.4132
881832.000021.02851.07381.7417e+0321.4130
891833.000021.01581.07441.7410e+0321.4128
901834.000021.00301.07511.7402e+0321.4126
911835.000020.99031.07571.7395e+0321.4123
921836.000020.97761.07641.7388e+0321.4121
931837.000020.96491.07701.7381e+0321.4119
941838.000020.95231.07761.7373e+0321.4117
951839.000020.93961.07831.7366e+0321.4114
961840.000020.92701.07891.7359e+0321.4112
971841.000020.91441.07961.7352e+0321.4110
981842.000020.90171.08021.7344e+0321.4108
991843.000020.88921.08081.7337e+0321.4105
1001844.000020.87661.08151.7330e+0321.4103
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11[ ]
12[ ]
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 216×6 table
 IDtIaIfNT
119092.98721.06659.549399.1687
2190.000092.98711.06659.690398.2505
3190.000092.98691.06659.829997.4927
4190.000092.98671.06659.968396.8706
5190.000092.98641.066510.251695.8754
6190.000092.98601.066510.532095.2143
7190.000092.98571.066510.810594.7877
8190.000092.98531.066511.087594.5158
9190.000192.98461.066511.613494.2601
10190.000192.98391.066512.138094.1496
11190.000192.98311.066512.662194.0893
12190.000192.98231.066513.186194.0560
13190.000192.98151.066513.709894.0414
14190.000292.97851.066515.398294.0255
15190.000292.97531.066517.086394.0286
16190.000392.97171.066518.774394.0274
17190.000392.96791.066520.462394.0228
18190.000892.91981.066533.772693.9735
19190.001292.85321.066547.070493.9062
20190.001692.76861.066560.352593.8206
21190.003192.36301.0665105.816093.4104
22190.004591.78141.0665150.961092.8223
23190.006091.04301.0665195.683692.0754
24190.007490.16831.0665239.889891.1908
25190.011587.10551.0665361.735688.0933
26190.015683.46431.0665477.492784.4108
27190.019779.52251.0665586.329280.4243
28190.023975.46991.0665687.886776.3258
29190.028071.43451.0665782.113072.2446
30190.034765.04521.0665921.409665.7829
31190.041559.16331.06651.0425e+0359.8342
32190.048253.89051.06651.1469e+0354.5016
33190.055049.23781.06651.2367e+0349.7962
34190.061745.17421.06651.3135e+0345.6865
35190.073939.15281.06651.4251e+0339.5968
36190.086234.59351.06651.5084e+0334.9858
37190.098431.17511.06651.5704e+0331.5286
38190.110628.61741.06651.6167e+0328.9419
39190.122826.70501.06651.6511e+0327.0078
40190.141824.66761.06651.6876e+0324.9473
41190.160923.38631.06651.7106e+0323.6515
42190.179922.57311.06651.7253e+0322.8291
43190.198922.05291.06651.7346e+0322.3030
44190.217921.72181.06651.7404e+0321.9682
45190.248121.44221.06651.7453e+0321.6853
46190.278321.31261.06651.7477e+0321.5543
47190.308421.24441.06651.7490e+0321.4853
48190.338621.20471.06651.7497e+0321.4452
49190.368821.18451.06651.7500e+0321.4248
50190.456821.16801.06651.7502e+0321.4080
51190.544821.17541.06651.7500e+0321.4156
52190.632821.18091.06651.7499e+0321.4211
53190.720821.18041.06651.7500e+0321.4206
54191.165121.17731.06651.7500e+0321.4174
55191.609521.17701.06651.7500e+0321.4171
56192.053821.17711.06651.7500e+0321.4172
57193.053821.17711.06651.7500e+0321.4173
58194.053821.17711.06651.7500e+0321.4173
59195.053821.17711.06651.7500e+0321.4173
60196.053821.17711.06651.7500e+0321.4173
61197.053821.17711.06651.7500e+0321.4173
62198.053821.17711.06651.7500e+0321.4173
63199.053821.17711.06651.7500e+0321.4173
641910.000021.17711.06651.7500e+0321.4173
651910.000021.17711.06651.7500e+0321.4173
661910.000021.17711.06651.7500e+0321.4173
671911.000021.15731.06731.7491e+0321.4145
681912.000021.13111.06861.7477e+0321.4130
691913.000021.10321.07001.7461e+0321.4123
701914.000021.07491.07141.7445e+0321.4118
711915.000021.04651.07281.7429e+0321.4113
721916.000021.01811.07421.7413e+0321.4108
731917.000020.98991.07561.7397e+0321.4103
741918.000020.96171.07711.7380e+0321.4098
751919.000020.93351.07851.7364e+0321.4093
761920.000020.90551.07991.7348e+0321.4088
771921.000020.87751.08131.7332e+0321.4083
781922.000020.84961.08281.7316e+0321.4079
791923.000020.82181.08421.7300e+0321.4074
801924.000020.79411.08561.7284e+0321.4069
811925.000020.76641.08701.7268e+0321.4064
821926.000020.73881.08841.7252e+0321.4059
831927.000020.71121.08991.7236e+0321.4054
841928.000020.68381.09131.7220e+0321.4049
851929.000020.65641.09271.7204e+0321.4044
861930.000020.62911.09411.7188e+0321.4040
871931.000020.60191.09551.7173e+0321.4035
881932.000020.57471.09701.7157e+0321.4030
891933.000020.54761.09841.7141e+0321.4025
901934.000020.52061.09981.7125e+0321.4020
911935.000020.49361.10121.7109e+0321.4015
921936.000020.46671.10271.7094e+0321.4011
931937.000020.43991.10411.7078e+0321.4006
941938.000020.41311.10551.7062e+0321.4001
951939.000020.38651.10691.7047e+0321.3996
961940.000020.35991.10831.7031e+0321.3991
971941.000020.33331.10981.7015e+0321.3987
981942.000020.30681.11121.7000e+0321.3982
991943.000020.28041.11261.6984e+0321.3977
1001944.000020.25411.11401.6969e+0321.3972
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12[ ]
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 226×6 table
 IDtIaIfNT
12092.98721.06659.549399.1687
220.000092.98711.06659.690398.2505
320.000092.98691.06659.829997.4927
420.000092.98671.06659.968396.8706
520.000092.98641.066510.251695.8754
620.000092.98601.066510.532095.2143
720.000092.98571.066510.810594.7877
820.000092.98531.066511.087594.5158
920.000192.98461.066511.613494.2601
1020.000192.98391.066512.138094.1496
1120.000192.98311.066512.662194.0893
1220.000192.98231.066513.186194.0560
1320.000192.98151.066513.709894.0414
1420.000292.97851.066515.398294.0255
1520.000292.97531.066517.086394.0286
1620.000392.97171.066518.774394.0274
1720.000392.96791.066520.462394.0228
1820.000892.91981.066533.772693.9735
1920.001292.85321.066547.070493.9062
2020.001692.76861.066560.352593.8206
2120.003192.36301.0665105.816093.4104
2220.004591.78141.0665150.961092.8223
2320.006091.04301.0665195.683692.0754
2420.007490.16831.0665239.889891.1908
2520.011587.10551.0665361.735688.0933
2620.015683.46431.0665477.492784.4108
2720.019779.52251.0665586.329280.4243
2820.023975.46991.0665687.886776.3258
2920.028071.43451.0665782.113072.2446
3020.034765.04521.0665921.409665.7829
3120.041559.16331.06651.0425e+0359.8342
3220.048253.89051.06651.1469e+0354.5016
3320.055049.23781.06651.2367e+0349.7962
3420.061745.17421.06651.3135e+0345.6865
3520.073939.15281.06651.4251e+0339.5968
3620.086234.59351.06651.5084e+0334.9858
3720.098431.17511.06651.5704e+0331.5286
3820.110628.61741.06651.6167e+0328.9419
3920.122826.70501.06651.6511e+0327.0078
4020.141824.66761.06651.6876e+0324.9473
4120.160923.38631.06651.7106e+0323.6515
4220.179922.57311.06651.7253e+0322.8291
4320.198922.05291.06651.7346e+0322.3030
4420.217921.72181.06651.7404e+0321.9682
4520.248121.44221.06651.7453e+0321.6853
4620.278321.31261.06651.7477e+0321.5543
4720.308421.24441.06651.7490e+0321.4853
4820.338621.20471.06651.7497e+0321.4452
4920.368821.18451.06651.7500e+0321.4248
5020.456821.16801.06651.7502e+0321.4080
5120.544821.17541.06651.7500e+0321.4156
5220.632821.18091.06651.7499e+0321.4211
5320.720821.18041.06651.7500e+0321.4206
5421.165121.17731.06651.7500e+0321.4174
5521.609521.17701.06651.7500e+0321.4171
5622.053821.17711.06651.7500e+0321.4172
5723.053821.17711.06651.7500e+0321.4173
5824.053821.17711.06651.7500e+0321.4173
5925.053821.17711.06651.7500e+0321.4173
6026.053821.17711.06651.7500e+0321.4173
6127.053821.17711.06651.7500e+0321.4173
6228.053821.17711.06651.7500e+0321.4173
6329.053821.17711.06651.7500e+0321.4173
64210.000021.17711.06651.7500e+0321.4173
65210.000021.17711.06651.7500e+0321.4173
66210.000021.17711.06651.7500e+0321.4173
67211.000021.18771.06651.7535e+0321.4280
68212.000021.18861.06651.7573e+0321.4289
69213.000021.18921.06651.7611e+0321.4295
70214.000021.19021.06651.7648e+0321.4305
71215.000021.19141.06651.7686e+0321.4317
72216.000021.19251.06651.7723e+0321.4329
73217.000021.19371.06651.7761e+0321.4340
74218.000021.19481.06651.7798e+0321.4352
75219.000021.19601.06651.7836e+0321.4363
76220.000021.19711.06651.7873e+0321.4375
77221.000021.19831.06651.7911e+0321.4387
78222.000021.19941.06651.7948e+0321.4398
79223.000021.20061.06651.7986e+0321.4410
80224.000021.20171.06651.8023e+0321.4421
81225.000021.20291.06651.8061e+0321.4433
82226.000021.20401.06651.8098e+0321.4445
83227.000021.20511.06651.8136e+0321.4456
84228.000021.20631.06651.8173e+0321.4468
85229.000021.20741.06651.8211e+0321.4479
86230.000021.20861.06651.8248e+0321.4491
87231.000021.20971.06651.8286e+0321.4503
88232.000021.21091.06651.8323e+0321.4514
89233.000021.21201.06651.8361e+0321.4526
90234.000021.21321.06651.8398e+0321.4537
91235.000021.21431.06651.8436e+0321.4549
92236.000021.21551.06651.8473e+0321.4561
93237.000021.21661.06651.8511e+0321.4572
94238.000021.21781.06651.8548e+0321.4584
95239.000021.21891.06651.8585e+0321.4595
96240.000021.22001.06651.8623e+0321.4607
97241.000021.22121.06651.8660e+0321.4618
98242.000021.22231.06651.8698e+0321.4630
99243.000021.22351.06651.8735e+0321.4642
100244.000021.22461.06651.8773e+0321.4653
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13[ ]
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 326×6 table
 IDtIaIfNT
120092.98721.06659.549399.1687
2200.000092.98711.06659.690398.2505
3200.000092.98691.06659.829997.4927
4200.000092.98671.06659.968396.8706
5200.000092.98641.066510.251695.8754
6200.000092.98601.066510.532095.2143
7200.000092.98571.066510.810594.7877
8200.000092.98531.066511.087594.5158
9200.000192.98461.066511.613494.2601
10200.000192.98391.066512.138094.1496
11200.000192.98311.066512.662194.0893
12200.000192.98231.066513.186194.0560
13200.000192.98151.066513.709894.0414
14200.000292.97851.066515.398294.0255
15200.000292.97531.066517.086394.0286
16200.000392.97171.066518.774394.0274
17200.000392.96791.066520.462394.0228
18200.000892.91981.066533.772693.9735
19200.001292.85321.066547.070493.9062
20200.001692.76861.066560.352593.8206
21200.003192.36301.0665105.816093.4104
22200.004591.78141.0665150.961092.8223
23200.006091.04301.0665195.683692.0754
24200.007490.16831.0665239.889891.1908
25200.011587.10551.0665361.735688.0933
26200.015683.46431.0665477.492784.4108
27200.019779.52251.0665586.329280.4243
28200.023975.46991.0665687.886776.3258
29200.028071.43451.0665782.113072.2446
30200.034765.04521.0665921.409665.7829
31200.041559.16331.06651.0425e+0359.8342
32200.048253.89051.06651.1469e+0354.5016
33200.055049.23781.06651.2367e+0349.7962
34200.061745.17421.06651.3135e+0345.6865
35200.073939.15281.06651.4251e+0339.5968
36200.086234.59351.06651.5084e+0334.9858
37200.098431.17511.06651.5704e+0331.5286
38200.110628.61741.06651.6167e+0328.9419
39200.122826.70501.06651.6511e+0327.0078
40200.141824.66761.06651.6876e+0324.9473
41200.160923.38631.06651.7106e+0323.6515
42200.179922.57311.06651.7253e+0322.8291
43200.198922.05291.06651.7346e+0322.3030
44200.217921.72181.06651.7404e+0321.9682
45200.248121.44221.06651.7453e+0321.6853
46200.278321.31261.06651.7477e+0321.5543
47200.308421.24441.06651.7490e+0321.4853
48200.338621.20471.06651.7497e+0321.4452
49200.368821.18451.06651.7500e+0321.4248
50200.456821.16801.06651.7502e+0321.4080
51200.544821.17541.06651.7500e+0321.4156
52200.632821.18091.06651.7499e+0321.4211
53200.720821.18041.06651.7500e+0321.4206
54201.165121.17731.06651.7500e+0321.4174
55201.609521.17701.06651.7500e+0321.4171
56202.053821.17711.06651.7500e+0321.4172
57203.053821.17711.06651.7500e+0321.4173
58204.053821.17711.06651.7500e+0321.4173
59205.053821.17711.06651.7500e+0321.4173
60206.053821.17711.06651.7500e+0321.4173
61207.053821.17711.06651.7500e+0321.4173
62208.053821.17711.06651.7500e+0321.4173
63209.053821.17711.06651.7500e+0321.4173
642010.053821.17711.06651.7500e+0321.4173
652011.053821.17711.06651.7500e+0321.4173
662012.053821.17711.06651.7500e+0321.4173
672013.053821.17711.06651.7500e+0321.4173
682014.053821.17711.06651.7500e+0321.4173
692015.000021.17711.06651.7500e+0321.4173
702015.000021.17711.06651.7500e+0321.4173
712015.000021.17711.06651.7500e+0321.4173
722016.000021.17221.06671.7498e+0321.4166
732017.000021.16561.06701.7495e+0321.4162
742018.000021.15861.06731.7491e+0321.4160
752019.000021.15151.06771.7487e+0321.4159
762020.000021.14431.06811.7482e+0321.4158
772021.000021.13721.06841.7478e+0321.4157
782022.000021.13001.06881.7474e+0321.4155
792023.000021.12281.06911.7470e+0321.4154
802024.000021.11571.06951.7466e+0321.4153
812025.000021.10861.06981.7462e+0321.4152
822026.000021.10141.07021.7458e+0321.4150
832027.000021.09431.07051.7454e+0321.4149
842028.000021.08721.07091.7450e+0321.4148
852029.000021.08001.07131.7446e+0321.4146
862030.000021.07291.07161.7442e+0321.4145
872031.000021.06581.07201.7438e+0321.4144
882032.000021.05871.07231.7434e+0321.4143
892033.000021.05161.07271.7430e+0321.4141
902034.000021.04451.07301.7426e+0321.4140
912035.000021.03741.07341.7422e+0321.4139
922036.000021.03031.07371.7417e+0321.4138
932037.000021.02331.07411.7413e+0321.4136
942038.000021.01621.07451.7409e+0321.4135
952039.000021.00911.07481.7405e+0321.4134
962040.000021.00201.07521.7401e+0321.4133
972041.000020.99501.07551.7397e+0321.4131
982042.000020.98791.07591.7393e+0321.4130
992043.000020.98091.07621.7389e+0321.4129
1002044.000020.97381.07661.7385e+0321.4128
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13326×6 table
14[ ]
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 356×6 table
 IDtIaIfNT
121092.98721.06659.549399.1687
2210.000092.98711.06659.690398.2505
3210.000092.98691.06659.829997.4927
4210.000092.98671.06659.968396.8706
5210.000092.98641.066510.251695.8754
6210.000092.98601.066510.532095.2143
7210.000092.98571.066510.810594.7877
8210.000092.98531.066511.087594.5158
9210.000192.98461.066511.613494.2601
10210.000192.98391.066512.138094.1496
11210.000192.98311.066512.662194.0893
12210.000192.98231.066513.186194.0560
13210.000192.98151.066513.709894.0414
14210.000292.97851.066515.398294.0255
15210.000292.97531.066517.086394.0286
16210.000392.97171.066518.774394.0274
17210.000392.96791.066520.462394.0228
18210.000892.91981.066533.772693.9735
19210.001292.85321.066547.070493.9062
20210.001692.76861.066560.352593.8206
21210.003192.36301.0665105.816093.4104
22210.004591.78141.0665150.961092.8223
23210.006091.04301.0665195.683692.0754
24210.007490.16831.0665239.889891.1908
25210.011587.10551.0665361.735688.0933
26210.015683.46431.0665477.492784.4108
27210.019779.52251.0665586.329280.4243
28210.023975.46991.0665687.886776.3258
29210.028071.43451.0665782.113072.2446
30210.034765.04521.0665921.409665.7829
31210.041559.16331.06651.0425e+0359.8342
32210.048253.89051.06651.1469e+0354.5016
33210.055049.23781.06651.2367e+0349.7962
34210.061745.17421.06651.3135e+0345.6865
35210.073939.15281.06651.4251e+0339.5968
36210.086234.59351.06651.5084e+0334.9858
37210.098431.17511.06651.5704e+0331.5286
38210.110628.61741.06651.6167e+0328.9419
39210.122826.70501.06651.6511e+0327.0078
40210.141824.66761.06651.6876e+0324.9473
41210.160923.38631.06651.7106e+0323.6515
42210.179922.57311.06651.7253e+0322.8291
43210.198922.05291.06651.7346e+0322.3030
44210.217921.72181.06651.7404e+0321.9682
45210.248121.44221.06651.7453e+0321.6853
46210.278321.31261.06651.7477e+0321.5543
47210.308421.24441.06651.7490e+0321.4853
48210.338621.20471.06651.7497e+0321.4452
49210.368821.18451.06651.7500e+0321.4248
50210.456821.16801.06651.7502e+0321.4080
51210.544821.17541.06651.7500e+0321.4156
52210.632821.18091.06651.7499e+0321.4211
53210.720821.18041.06651.7500e+0321.4206
54211.165121.17731.06651.7500e+0321.4174
55211.609521.17701.06651.7500e+0321.4171
56212.053821.17711.06651.7500e+0321.4172
57213.053821.17711.06651.7500e+0321.4173
58214.053821.17711.06651.7500e+0321.4173
59215.053821.17711.06651.7500e+0321.4173
60216.053821.17711.06651.7500e+0321.4173
61217.053821.17711.06651.7500e+0321.4173
62218.053821.17711.06651.7500e+0321.4173
63219.053821.17711.06651.7500e+0321.4173
642110.053821.17711.06651.7500e+0321.4173
652111.053821.17711.06651.7500e+0321.4173
662112.053821.17711.06651.7500e+0321.4173
672113.053821.17711.06651.7500e+0321.4173
682114.053821.17711.06651.7500e+0321.4173
692115.053821.17711.06651.7500e+0321.4173
702116.053821.17711.06651.7500e+0321.4173
712117.053821.17711.06651.7500e+0321.4173
722118.053821.17711.06651.7500e+0321.4173
732119.053821.17711.06651.7500e+0321.4173
742120.000021.17711.06651.7500e+0321.4173
752120.000021.17711.06651.7500e+0321.4173
762120.000021.17711.06651.7500e+0321.4173
772121.000021.17321.06661.7499e+0321.4167
782122.000021.16791.06691.7496e+0321.4164
792123.000021.16231.06721.7493e+0321.4163
802124.000021.15661.06751.7489e+0321.4162
812125.000021.15091.06771.7486e+0321.4161
822126.000021.14511.06801.7483e+0321.4160
832127.000021.13941.06831.7480e+0321.4159
842128.000021.13371.06861.7476e+0321.4158
852129.000021.12801.06891.7473e+0321.4157
862130.000021.12221.06921.7470e+0321.4156
872131.000021.11651.06941.7467e+0321.4155
882132.000021.11081.06971.7463e+0321.4154
892133.000021.10511.07001.7460e+0321.4153
902134.000021.09941.07031.7457e+0321.4152
912135.000021.09371.07061.7453e+0321.4151
922136.000021.08801.07091.7450e+0321.4150
932137.000021.08231.07121.7447e+0321.4149
942138.000021.07661.07141.7444e+0321.4148
952139.000021.07091.07171.7440e+0321.4147
962140.000021.06521.07201.7437e+0321.4146
972141.000021.05951.07231.7434e+0321.4145
982142.000021.05381.07261.7431e+0321.4144
992143.000021.04821.07291.7428e+0321.4143
1002144.000021.04251.07311.7424e+0321.4142
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13326×6 table
14356×6 table
15[ ]
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 206×6 table
 IDtIaIfNT
122092.98721.06659.549399.1687
2220.000092.98711.06659.690398.2505
3220.000092.98691.06659.829997.4927
4220.000092.98671.06659.968396.8706
5220.000092.98641.066510.251695.8754
6220.000092.98601.066510.532095.2143
7220.000092.98571.066510.810594.7877
8220.000092.98531.066511.087594.5158
9220.000192.98461.066511.613494.2601
10220.000192.98391.066512.138094.1496
11220.000192.98311.066512.662194.0893
12220.000192.98231.066513.186194.0560
13220.000192.98151.066513.709894.0414
14220.000292.97851.066515.398294.0255
15220.000292.97531.066517.086394.0286
16220.000392.97171.066518.774394.0274
17220.000392.96791.066520.462394.0228
18220.000892.91981.066533.772693.9735
19220.001292.85321.066547.070493.9062
20220.001692.76861.066560.352593.8206
21220.003192.36301.0665105.816093.4104
22220.004591.78141.0665150.961092.8223
23220.006091.04301.0665195.683692.0754
24220.007490.16831.0665239.889891.1908
25220.011587.10551.0665361.735688.0933
26220.015683.46431.0665477.492784.4108
27220.019779.52251.0665586.329280.4243
28220.023975.46991.0665687.886776.3258
29220.028071.43451.0665782.113072.2446
30220.034765.04521.0665921.409665.7829
31220.041559.16331.06651.0425e+0359.8342
32220.048253.89051.06651.1469e+0354.5016
33220.055049.23781.06651.2367e+0349.7962
34220.061745.17421.06651.3135e+0345.6865
35220.073939.15281.06651.4251e+0339.5968
36220.086234.59351.06651.5084e+0334.9858
37220.098431.17511.06651.5704e+0331.5286
38220.110628.61741.06651.6167e+0328.9419
39220.122826.70501.06651.6511e+0327.0078
40220.141824.66761.06651.6876e+0324.9473
41220.160923.38631.06651.7106e+0323.6515
42220.179922.57311.06651.7253e+0322.8291
43220.198922.05291.06651.7346e+0322.3030
44220.217921.72181.06651.7404e+0321.9682
45220.248121.44221.06651.7453e+0321.6853
46220.278321.31261.06651.7477e+0321.5543
47220.308421.24441.06651.7490e+0321.4853
48220.338621.20471.06651.7497e+0321.4452
49220.368821.18451.06651.7500e+0321.4248
50220.456821.16801.06651.7502e+0321.4080
51220.544821.17541.06651.7500e+0321.4156
52220.632821.18091.06651.7499e+0321.4211
53220.720821.18041.06651.7500e+0321.4206
54221.165121.17731.06651.7500e+0321.4174
55221.609521.17701.06651.7500e+0321.4171
56222.053821.17711.06651.7500e+0321.4172
57223.053821.17711.06651.7500e+0321.4173
58224.053821.17711.06651.7500e+0321.4173
59225.053821.17711.06651.7500e+0321.4173
60226.053821.17711.06651.7500e+0321.4173
61227.053821.17711.06651.7500e+0321.4173
62228.053821.17711.06651.7500e+0321.4173
63229.053821.17711.06651.7500e+0321.4173
642210.053821.17711.06651.7500e+0321.4173
652211.053821.17711.06651.7500e+0321.4173
662212.053821.17711.06651.7500e+0321.4173
672213.053821.17711.06651.7500e+0321.4173
682214.053821.17711.06651.7500e+0321.4173
692215.053821.17711.06651.7500e+0321.4173
702216.053821.17711.06651.7500e+0321.4173
712217.053821.17711.06651.7500e+0321.4173
722218.053821.17711.06651.7500e+0321.4173
732219.053821.17711.06651.7500e+0321.4173
742220.053821.17711.06651.7500e+0321.4173
752221.053821.17711.06651.7500e+0321.4173
762222.053821.17711.06651.7500e+0321.4173
772223.053821.17711.06651.7500e+0321.4173
782224.053821.17711.06651.7500e+0321.4173
792225.000021.17711.06651.7500e+0321.4173
802225.000021.17711.06651.7500e+0321.4173
812225.000021.17711.06651.7500e+0321.4173
822226.000021.14741.06781.7487e+0321.4131
832227.000021.10821.06961.7465e+0321.4109
842228.000021.06641.07171.7442e+0321.4099
852229.000021.02411.07381.7418e+0321.4091
862230.000020.98171.07601.7393e+0321.4083
872231.000020.93951.07811.7369e+0321.4076
882232.000020.89751.08021.7345e+0321.4069
892233.000020.85561.08241.7321e+0321.4061
902234.000020.81381.08451.7297e+0321.4054
912235.000020.77231.08661.7273e+0321.4047
922236.000020.73091.08881.7249e+0321.4039
932237.000020.68961.09091.7225e+0321.4032
942238.000020.64861.09301.7201e+0321.4025
952239.000020.60761.09521.7177e+0321.4018
962240.000020.56691.09731.7154e+0321.4011
972241.000020.52631.09941.7130e+0321.4003
982242.000020.48591.10161.7106e+0321.3996
992243.000020.44561.10371.7083e+0321.3989
1002244.000020.40551.10581.7059e+0321.3982
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13326×6 table
14356×6 table
15206×6 table
16[ ]
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 141×6 table
 IDtIaIfNT
123092.98721.06659.549399.1687
2230.000092.98711.06659.690398.2505
3230.000092.98691.06659.829997.4927
4230.000092.98671.06659.968396.8706
5230.000092.98641.066510.251695.8754
6230.000092.98601.066510.532095.2143
7230.000092.98571.066510.810594.7877
8230.000092.98531.066511.087594.5158
9230.000192.98461.066511.613494.2601
10230.000192.98391.066512.138094.1496
11230.000192.98311.066512.662194.0893
12230.000192.98231.066513.186194.0560
13230.000192.98151.066513.709894.0414
14230.000292.97851.066515.398294.0255
15230.000292.97531.066517.086394.0286
16230.000392.97171.066518.774394.0274
17230.000392.96791.066520.462394.0228
18230.000892.91981.066533.772693.9735
19230.001292.85321.066547.070493.9062
20230.001692.76861.066560.352593.8206
21230.003192.36301.0665105.816093.4104
22230.004591.78141.0665150.961092.8223
23230.006091.04301.0665195.683692.0754
24230.007490.16831.0665239.889891.1908
25230.011587.10551.0665361.735688.0933
26230.015683.46431.0665477.492784.4108
27230.019779.52251.0665586.329280.4243
28230.023975.46991.0665687.886776.3258
29230.028071.43451.0665782.113072.2446
30230.034765.04521.0665921.409665.7829
31230.041559.16331.06651.0425e+0359.8342
32230.048253.89051.06651.1469e+0354.5016
33230.055049.23781.06651.2367e+0349.7962
34230.061745.17421.06651.3135e+0345.6865
35230.073939.15281.06651.4251e+0339.5968
36230.086234.59351.06651.5084e+0334.9858
37230.098431.17511.06651.5704e+0331.5286
38230.110628.61741.06651.6167e+0328.9419
39230.122826.70501.06651.6511e+0327.0078
40230.141824.66761.06651.6876e+0324.9473
41230.160923.38631.06651.7106e+0323.6515
42230.179922.57311.06651.7253e+0322.8291
43230.198922.05291.06651.7346e+0322.3030
44230.217921.72181.06651.7404e+0321.9682
45230.248121.44221.06651.7453e+0321.6853
46230.278321.31261.06651.7477e+0321.5543
47230.308421.24441.06651.7490e+0321.4853
48230.338621.20471.06651.7497e+0321.4452
49230.368821.18451.06651.7500e+0321.4248
50230.456821.16801.06651.7502e+0321.4080
51230.544821.17541.06651.7500e+0321.4156
52230.632821.18091.06651.7499e+0321.4211
53230.720821.18041.06651.7500e+0321.4206
54231.165121.17731.06651.7500e+0321.4174
55231.609521.17701.06651.7500e+0321.4171
56232.053821.17711.06651.7500e+0321.4172
57233.053821.17711.06651.7500e+0321.4173
58234.053821.17711.06651.7500e+0321.4173
59235.053821.17711.06651.7500e+0321.4173
60236.053821.17711.06651.7500e+0321.4173
61237.053821.17711.06651.7500e+0321.4173
62238.053821.17711.06651.7500e+0321.4173
63239.053821.17711.06651.7500e+0321.4173
642310.053821.17711.06651.7500e+0321.4173
652311.053821.17711.06651.7500e+0321.4173
662312.053821.17711.06651.7500e+0321.4173
672313.053821.17711.06651.7500e+0321.4173
682314.053821.17711.06651.7500e+0321.4173
692315.000021.17711.06651.7500e+0321.4173
702315.000021.17711.06651.7500e+0321.4173
712315.000021.17711.06651.7500e+0321.4173
722316.000021.13261.06841.7480e+0321.4110
732317.000021.07381.07121.7448e+0321.4077
742318.000021.01151.07431.7413e+0321.4062
752319.000020.94841.07751.7377e+0321.4050
762320.000020.88541.08071.7340e+0321.4039
772321.000020.82271.08391.7304e+0321.4028
782322.000020.76031.08711.7268e+0321.4018
792323.000020.69841.09031.7232e+0321.4007
802324.000020.63681.09351.7197e+0321.3996
812325.000020.57551.09671.7161e+0321.3985
822326.000020.51471.09991.7125e+0321.3975
832327.000020.45421.10311.7090e+0321.3964
842328.000020.39401.10631.7055e+0321.3953
852329.000020.33421.10951.7019e+0321.3943
862330.000020.27471.11271.6984e+0321.3932
872331.000020.21561.11591.6950e+0321.3922
882332.000020.15681.11911.6915e+0321.3911
892333.000020.09841.12231.6880e+0321.3901
902334.000020.04021.12551.6845e+0321.3890
912335.000019.98251.12871.6811e+0321.3880
922336.000019.92501.13191.6777e+0321.3870
932337.000019.86791.13511.6742e+0321.3859
942338.000019.81111.13831.6708e+0321.3849
952339.000019.75461.14151.6674e+0321.3839
962340.000019.69851.14471.6641e+0321.3829
972341.000019.64261.14791.6607e+0321.3818
982342.000019.58711.15111.6573e+0321.3808
992343.000019.53191.15431.6540e+0321.3798
1002344.000019.47701.15751.6506e+0321.3788
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13326×6 table
14356×6 table
15206×6 table
16141×6 table
17[ ]
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 238×6 table
 IDtIaIfNT
125092.98721.06659.549399.1687
2250.000092.98711.06659.690398.2505
3250.000092.98691.06659.829997.4927
4250.000092.98671.06659.968396.8706
5250.000092.98641.066510.251695.8754
6250.000092.98601.066510.532095.2143
7250.000092.98571.066510.810594.7877
8250.000092.98531.066511.087594.5158
9250.000192.98461.066511.613494.2601
10250.000192.98391.066512.138094.1496
11250.000192.98311.066512.662194.0893
12250.000192.98231.066513.186194.0560
13250.000192.98151.066513.709894.0414
14250.000292.97851.066515.398294.0255
15250.000292.97531.066517.086394.0286
16250.000392.97171.066518.774394.0274
17250.000392.96791.066520.462394.0228
18250.000892.91981.066533.772693.9735
19250.001292.85321.066547.070493.9062
20250.001692.76861.066560.352593.8206
21250.003192.36301.0665105.816093.4104
22250.004591.78141.0665150.961092.8223
23250.006091.04301.0665195.683692.0754
24250.007490.16831.0665239.889891.1908
25250.011587.10551.0665361.735688.0933
26250.015683.46431.0665477.492784.4108
27250.019779.52251.0665586.329280.4243
28250.023975.46991.0665687.886776.3258
29250.028071.43451.0665782.113072.2446
30250.034765.04521.0665921.409665.7829
31250.041559.16331.06651.0425e+0359.8342
32250.048253.89051.06651.1469e+0354.5016
33250.055049.23781.06651.2367e+0349.7962
34250.061745.17421.06651.3135e+0345.6865
35250.073939.15281.06651.4251e+0339.5968
36250.086234.59351.06651.5084e+0334.9858
37250.098431.17511.06651.5704e+0331.5286
38250.110628.61741.06651.6167e+0328.9419
39250.122826.70501.06651.6511e+0327.0078
40250.141824.66761.06651.6876e+0324.9473
41250.160923.38631.06651.7106e+0323.6515
42250.179922.57311.06651.7253e+0322.8291
43250.198922.05291.06651.7346e+0322.3030
44250.217921.72181.06651.7404e+0321.9682
45250.248121.44221.06651.7453e+0321.6853
46250.278321.31261.06651.7477e+0321.5543
47250.308421.24441.06651.7490e+0321.4853
48250.338621.20471.06651.7497e+0321.4452
49250.368821.18451.06651.7500e+0321.4248
50250.456821.16801.06651.7502e+0321.4080
51250.544821.17541.06651.7500e+0321.4156
52250.632821.18091.06651.7499e+0321.4211
53250.720821.18041.06651.7500e+0321.4206
54251.165121.17731.06651.7500e+0321.4174
55251.609521.17701.06651.7500e+0321.4171
56252.053821.17711.06651.7500e+0321.4172
57253.053821.17711.06651.7500e+0321.4173
58254.053821.17711.06651.7500e+0321.4173
59255.053821.17711.06651.7500e+0321.4173
60256.053821.17711.06651.7500e+0321.4173
61257.053821.17711.06651.7500e+0321.4173
62258.053821.17711.06651.7500e+0321.4173
63259.053821.17711.06651.7500e+0321.4173
642510.053821.17711.06651.7500e+0321.4173
652511.053821.17711.06651.7500e+0321.4173
662512.053821.17711.06651.7500e+0321.4173
672513.053821.17711.06651.7500e+0321.4173
682514.053821.17711.06651.7500e+0321.4173
692515.053821.17711.06651.7500e+0321.4173
702516.053821.17711.06651.7500e+0321.4173
712517.053821.17711.06651.7500e+0321.4173
722518.053821.17711.06651.7500e+0321.4173
732519.053821.17711.06651.7500e+0321.4173
742520.053821.17711.06651.7500e+0321.4173
752521.053821.17711.06651.7500e+0321.4173
762522.053821.17711.06651.7500e+0321.4173
772523.053821.17711.06651.7500e+0321.4173
782524.053821.17711.06651.7500e+0321.4173
792525.053821.17711.06651.7500e+0321.4173
802526.053821.17711.06651.7500e+0321.4173
812527.000021.17711.06651.7500e+0321.4173
822527.000021.17711.06651.7500e+0321.4173
832527.000021.17711.06651.7500e+0321.4173
842528.000021.15881.06731.7492e+0321.4147
852529.000021.13461.06841.7479e+0321.4134
862530.000021.10871.06971.7464e+0321.4127
872531.000021.08251.07101.7449e+0321.4122
882532.000021.05621.07231.7434e+0321.4117
892533.000021.03001.07361.7419e+0321.4113
902534.000021.00381.07501.7404e+0321.4108
912535.000020.97771.07631.7389e+0321.4104
922536.000020.95161.07761.7374e+0321.4099
932537.000020.92561.07891.7360e+0321.4095
942538.000020.89971.08021.7345e+0321.4090
952539.000020.87381.08151.7330e+0321.4086
962540.000020.84801.08281.7315e+0321.4081
972541.000020.82231.08421.7300e+0321.4076
982542.000020.79661.08551.7285e+0321.4072
992543.000020.77101.08681.7270e+0321.4067
1002544.000020.74551.08811.7256e+0321.4063
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13326×6 table
14356×6 table
15206×6 table
16141×6 table
17238×6 table
18[ ]
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 111×6 table
 IDtIaIfNT
126092.98721.06659.549399.1687
2260.000092.98711.06659.690398.2505
3260.000092.98691.06659.829997.4927
4260.000092.98671.06659.968396.8706
5260.000092.98641.066510.251695.8754
6260.000092.98601.066510.532095.2143
7260.000092.98571.066510.810594.7877
8260.000092.98531.066511.087594.5158
9260.000192.98461.066511.613494.2601
10260.000192.98391.066512.138094.1496
11260.000192.98311.066512.662194.0893
12260.000192.98231.066513.186194.0560
13260.000192.98151.066513.709894.0414
14260.000292.97851.066515.398294.0255
15260.000292.97531.066517.086394.0286
16260.000392.97171.066518.774394.0274
17260.000392.96791.066520.462394.0228
18260.000892.91981.066533.772693.9735
19260.001292.85321.066547.070493.9062
20260.001692.76861.066560.352593.8206
21260.003192.36301.0665105.816093.4104
22260.004591.78141.0665150.961092.8223
23260.006091.04301.0665195.683692.0754
24260.007490.16831.0665239.889891.1908
25260.011587.10551.0665361.735688.0933
26260.015683.46431.0665477.492784.4108
27260.019779.52251.0665586.329280.4243
28260.023975.46991.0665687.886776.3258
29260.028071.43451.0665782.113072.2446
30260.034765.04521.0665921.409665.7829
31260.041559.16331.06651.0425e+0359.8342
32260.048253.89051.06651.1469e+0354.5016
33260.055049.23781.06651.2367e+0349.7962
34260.061745.17421.06651.3135e+0345.6865
35260.073939.15281.06651.4251e+0339.5968
36260.086234.59351.06651.5084e+0334.9858
37260.098431.17511.06651.5704e+0331.5286
38260.110628.61741.06651.6167e+0328.9419
39260.122826.70501.06651.6511e+0327.0078
40260.141824.66761.06651.6876e+0324.9473
41260.160923.38631.06651.7106e+0323.6515
42260.179922.57311.06651.7253e+0322.8291
43260.198922.05291.06651.7346e+0322.3030
44260.217921.72181.06651.7404e+0321.9682
45260.248121.44221.06651.7453e+0321.6853
46260.278321.31261.06651.7477e+0321.5543
47260.308421.24441.06651.7490e+0321.4853
48260.338621.20471.06651.7497e+0321.4452
49260.368821.18451.06651.7500e+0321.4248
50260.456821.16801.06651.7502e+0321.4080
51260.544821.17541.06651.7500e+0321.4156
52260.632821.18091.06651.7499e+0321.4211
53260.720821.18041.06651.7500e+0321.4206
54261.165121.17731.06651.7500e+0321.4174
55261.609521.17701.06651.7500e+0321.4171
56262.053821.17711.06651.7500e+0321.4172
57263.053821.17711.06651.7500e+0321.4173
58264.053821.17711.06651.7500e+0321.4173
59265.053821.17711.06651.7500e+0321.4173
60266.053821.17711.06651.7500e+0321.4173
61267.053821.17711.06651.7500e+0321.4173
62268.053821.17711.06651.7500e+0321.4173
63269.053821.17711.06651.7500e+0321.4173
642610.053821.17711.06651.7500e+0321.4173
652611.053821.17711.06651.7500e+0321.4173
662612.053821.17711.06651.7500e+0321.4173
672613.053821.17711.06651.7500e+0321.4173
682614.053821.17711.06651.7500e+0321.4173
692615.053821.17711.06651.7500e+0321.4173
702616.053821.17711.06651.7500e+0321.4173
712617.053821.17711.06651.7500e+0321.4173
722618.053821.17711.06651.7500e+0321.4173
732619.053821.17711.06651.7500e+0321.4173
742620.053821.17711.06651.7500e+0321.4173
752621.053821.17711.06651.7500e+0321.4173
762622.053821.17711.06651.7500e+0321.4173
772623.053821.17711.06651.7500e+0321.4173
782624.053821.17711.06651.7500e+0321.4173
792625.000021.17711.06651.7500e+0321.4173
802625.000021.17711.06651.7500e+0321.4173
812625.000021.17711.06651.7500e+0321.4173
822625.740021.11041.06931.7471e+0321.4056
832626.480021.01921.07361.7423e+0321.3988
842627.219920.91961.07851.7368e+0321.3950
852627.959920.81821.08361.7310e+0321.3929
862628.959920.68091.09071.7230e+0321.3905
872629.959920.54491.09781.7151e+0321.3881
882630.959920.41061.10491.7072e+0321.3859
892631.959920.27791.11201.6994e+0321.3836
902632.959920.14701.11911.6917e+0321.3813
912633.959920.01761.12621.6840e+0321.3791
922634.959919.89001.13331.6763e+0321.3768
932635.959919.76391.14051.6688e+0321.3746
942636.959919.63951.14761.6612e+0321.3724
952637.959919.51661.15471.6538e+0321.3703
962638.959919.39521.16181.6464e+0321.3681
972639.959919.27531.16891.6390e+0321.3660
982640.959919.15681.17601.6317e+0321.3638
992641.959919.03981.18311.6245e+0321.3617
1002642.959918.92421.19021.6173e+0321.3596
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13326×6 table
14356×6 table
15206×6 table
16141×6 table
17238×6 table
18111×6 table
19[ ]
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 193×6 table
 IDtIaIfNT
127092.98721.06659.549399.1687
2270.000092.98711.06659.690398.2505
3270.000092.98691.06659.829997.4927
4270.000092.98671.06659.968396.8706
5270.000092.98641.066510.251695.8754
6270.000092.98601.066510.532095.2143
7270.000092.98571.066510.810594.7877
8270.000092.98531.066511.087594.5158
9270.000192.98461.066511.613494.2601
10270.000192.98391.066512.138094.1496
11270.000192.98311.066512.662194.0893
12270.000192.98231.066513.186194.0560
13270.000192.98151.066513.709894.0414
14270.000292.97851.066515.398294.0255
15270.000292.97531.066517.086394.0286
16270.000392.97171.066518.774394.0274
17270.000392.96791.066520.462394.0228
18270.000892.91981.066533.772693.9735
19270.001292.85321.066547.070493.9062
20270.001692.76861.066560.352593.8206
21270.003192.36301.0665105.816093.4104
22270.004591.78141.0665150.961092.8223
23270.006091.04301.0665195.683692.0754
24270.007490.16831.0665239.889891.1908
25270.011587.10551.0665361.735688.0933
26270.015683.46431.0665477.492784.4108
27270.019779.52251.0665586.329280.4243
28270.023975.46991.0665687.886776.3258
29270.028071.43451.0665782.113072.2446
30270.034765.04521.0665921.409665.7829
31270.041559.16331.06651.0425e+0359.8342
32270.048253.89051.06651.1469e+0354.5016
33270.055049.23781.06651.2367e+0349.7962
34270.061745.17421.06651.3135e+0345.6865
35270.073939.15281.06651.4251e+0339.5968
36270.086234.59351.06651.5084e+0334.9858
37270.098431.17511.06651.5704e+0331.5286
38270.110628.61741.06651.6167e+0328.9419
39270.122826.70501.06651.6511e+0327.0078
40270.141824.66761.06651.6876e+0324.9473
41270.160923.38631.06651.7106e+0323.6515
42270.179922.57311.06651.7253e+0322.8291
43270.198922.05291.06651.7346e+0322.3030
44270.217921.72181.06651.7404e+0321.9682
45270.248121.44221.06651.7453e+0321.6853
46270.278321.31261.06651.7477e+0321.5543
47270.308421.24441.06651.7490e+0321.4853
48270.338621.20471.06651.7497e+0321.4452
49270.368821.18451.06651.7500e+0321.4248
50270.456821.16801.06651.7502e+0321.4080
51270.544821.17541.06651.7500e+0321.4156
52270.632821.18091.06651.7499e+0321.4211
53270.720821.18041.06651.7500e+0321.4206
54271.165121.17731.06651.7500e+0321.4174
55271.609521.17701.06651.7500e+0321.4171
56272.053821.17711.06651.7500e+0321.4172
57273.053821.17711.06651.7500e+0321.4173
58274.053821.17711.06651.7500e+0321.4173
59275.053821.17711.06651.7500e+0321.4173
60276.053821.17711.06651.7500e+0321.4173
61277.053821.17711.06651.7500e+0321.4173
62278.053821.17711.06651.7500e+0321.4173
63279.053821.17711.06651.7500e+0321.4173
642710.053821.17711.06651.7500e+0321.4173
652711.053821.17711.06651.7500e+0321.4173
662712.053821.17711.06651.7500e+0321.4173
672713.053821.17711.06651.7500e+0321.4173
682714.053821.17711.06651.7500e+0321.4173
692715.053821.17711.06651.7500e+0321.4173
702716.053821.17711.06651.7500e+0321.4173
712717.053821.17711.06651.7500e+0321.4173
722718.053821.17711.06651.7500e+0321.4173
732719.053821.17711.06651.7500e+0321.4173
742720.053821.17711.06651.7500e+0321.4173
752721.053821.17711.06651.7500e+0321.4173
762722.053821.17711.06651.7500e+0321.4173
772723.053821.17711.06651.7500e+0321.4173
782724.053821.17711.06651.7500e+0321.4173
792725.053821.17711.06651.7500e+0321.4173
802726.053821.17711.06651.7500e+0321.4173
812727.053821.17711.06651.7500e+0321.4173
822728.053821.17711.06651.7500e+0321.4173
832729.053821.17711.06651.7500e+0321.4173
842730.000021.17711.06651.7500e+0321.4173
852730.000021.17711.06651.7500e+0321.4173
862730.000021.17711.06651.7500e+0321.4173
872731.000021.15091.06761.7488e+0321.4136
882732.000021.11621.06931.7470e+0321.4117
892733.000021.07931.07111.7449e+0321.4107
902734.000021.04181.07301.7427e+0321.4100
912735.000021.00431.07491.7406e+0321.4094
922736.000020.96701.07671.7384e+0321.4087
932737.000020.92971.07861.7363e+0321.4081
942738.000020.89261.08051.7342e+0321.4074
952739.000020.85561.08241.7320e+0321.4068
962740.000020.81871.08431.7299e+0321.4061
972741.000020.78201.08621.7278e+0321.4055
982742.000020.74531.08801.7257e+0321.4048
992743.000020.70891.08991.7236e+0321.4042
1002744.000020.67251.09181.7215e+0321.4036
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13326×6 table
14356×6 table
15206×6 table
16141×6 table
17238×6 table
18111×6 table
19193×6 table
20[ ]
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 581×6 table
 IDtIaIfNT
128092.98721.06659.549399.1687
2280.000092.98711.06659.690398.2505
3280.000092.98691.06659.829997.4927
4280.000092.98671.06659.968396.8706
5280.000092.98641.066510.251695.8754
6280.000092.98601.066510.532095.2143
7280.000092.98571.066510.810594.7877
8280.000092.98531.066511.087594.5158
9280.000192.98461.066511.613494.2601
10280.000192.98391.066512.138094.1496
11280.000192.98311.066512.662194.0893
12280.000192.98231.066513.186194.0560
13280.000192.98151.066513.709894.0414
14280.000292.97851.066515.398294.0255
15280.000292.97531.066517.086394.0286
16280.000392.97171.066518.774394.0274
17280.000392.96791.066520.462394.0228
18280.000892.91981.066533.772693.9735
19280.001292.85321.066547.070493.9062
20280.001692.76861.066560.352593.8206
21280.003192.36301.0665105.816093.4104
22280.004591.78141.0665150.961092.8223
23280.006091.04301.0665195.683692.0754
24280.007490.16831.0665239.889891.1908
25280.011587.10551.0665361.735688.0933
26280.015683.46431.0665477.492784.4108
27280.019779.52251.0665586.329280.4243
28280.023975.46991.0665687.886776.3258
29280.028071.43451.0665782.113072.2446
30280.034765.04521.0665921.409665.7829
31280.041559.16331.06651.0425e+0359.8342
32280.048253.89051.06651.1469e+0354.5016
33280.055049.23781.06651.2367e+0349.7962
34280.061745.17421.06651.3135e+0345.6865
35280.073939.15281.06651.4251e+0339.5968
36280.086234.59351.06651.5084e+0334.9858
37280.098431.17511.06651.5704e+0331.5286
38280.110628.61741.06651.6167e+0328.9419
39280.122826.70501.06651.6511e+0327.0078
40280.141824.66761.06651.6876e+0324.9473
41280.160923.38631.06651.7106e+0323.6515
42280.179922.57311.06651.7253e+0322.8291
43280.198922.05291.06651.7346e+0322.3030
44280.217921.72181.06651.7404e+0321.9682
45280.248121.44221.06651.7453e+0321.6853
46280.278321.31261.06651.7477e+0321.5543
47280.308421.24441.06651.7490e+0321.4853
48280.338621.20471.06651.7497e+0321.4452
49280.368821.18451.06651.7500e+0321.4248
50280.456821.16801.06651.7502e+0321.4080
51280.544821.17541.06651.7500e+0321.4156
52280.632821.18091.06651.7499e+0321.4211
53280.720821.18041.06651.7500e+0321.4206
54281.165121.17731.06651.7500e+0321.4174
55281.609521.17701.06651.7500e+0321.4171
56282.053821.17711.06651.7500e+0321.4172
57283.053821.17711.06651.7500e+0321.4173
58284.053821.17711.06651.7500e+0321.4173
59285.053821.17711.06651.7500e+0321.4173
60286.053821.17711.06651.7500e+0321.4173
61287.053821.17711.06651.7500e+0321.4173
62288.053821.17711.06651.7500e+0321.4173
63289.053821.17711.06651.7500e+0321.4173
642810.000021.17711.06651.7500e+0321.4173
652810.000021.17711.06651.7500e+0321.4173
662810.000021.17711.06651.7500e+0321.4173
672811.000021.17221.06671.7498e+0321.4166
682812.000021.16561.06701.7495e+0321.4162
692813.000021.15861.06731.7491e+0321.4160
702814.000021.15151.06771.7487e+0321.4159
712815.000021.14431.06811.7482e+0321.4158
722816.000021.13721.06841.7478e+0321.4157
732817.000021.13001.06881.7474e+0321.4155
742818.000021.12281.06911.7470e+0321.4154
752819.000021.11571.06951.7466e+0321.4153
762820.000021.10861.06981.7462e+0321.4152
772821.000021.10141.07021.7458e+0321.4150
782822.000021.09431.07051.7454e+0321.4149
792823.000021.08721.07091.7450e+0321.4148
802824.000021.08001.07131.7446e+0321.4146
812825.000021.07291.07161.7442e+0321.4145
822826.000021.06581.07201.7438e+0321.4144
832827.000021.05871.07231.7434e+0321.4143
842828.000021.05161.07271.7430e+0321.4141
852829.000021.04451.07301.7426e+0321.4140
862830.000021.03741.07341.7422e+0321.4139
872831.000021.03031.07371.7417e+0321.4138
882832.000021.02331.07411.7413e+0321.4136
892833.000021.01621.07451.7409e+0321.4135
902834.000021.00911.07481.7405e+0321.4134
912835.000021.00201.07521.7401e+0321.4133
922836.000020.99501.07551.7397e+0321.4131
932837.000020.98791.07591.7393e+0321.4130
942838.000020.98091.07621.7389e+0321.4129
952839.000020.97381.07661.7385e+0321.4128
962840.000020.96681.07691.7381e+0321.4127
972841.000020.95971.07731.7377e+0321.4125
982842.000020.95271.07771.7373e+0321.4124
992843.000020.94571.07801.7369e+0321.4123
1002844.000020.93861.07841.7365e+0321.4122
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13326×6 table
14356×6 table
15206×6 table
16141×6 table
17238×6 table
18111×6 table
19193×6 table
20581×6 table
21[ ]
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 499×6 table
 IDtIaIfNT
129092.98721.06659.549399.1687
2290.000092.98711.06659.690398.2505
3290.000092.98691.06659.829997.4927
4290.000092.98671.06659.968396.8706
5290.000092.98641.066510.251695.8754
6290.000092.98601.066510.532095.2143
7290.000092.98571.066510.810594.7877
8290.000092.98531.066511.087594.5158
9290.000192.98461.066511.613494.2601
10290.000192.98391.066512.138094.1496
11290.000192.98311.066512.662194.0893
12290.000192.98231.066513.186194.0560
13290.000192.98151.066513.709894.0414
14290.000292.97851.066515.398294.0255
15290.000292.97531.066517.086394.0286
16290.000392.97171.066518.774394.0274
17290.000392.96791.066520.462394.0228
18290.000892.91981.066533.772693.9735
19290.001292.85321.066547.070493.9062
20290.001692.76861.066560.352593.8206
21290.003192.36301.0665105.816093.4104
22290.004591.78141.0665150.961092.8223
23290.006091.04301.0665195.683692.0754
24290.007490.16831.0665239.889891.1908
25290.011587.10551.0665361.735688.0933
26290.015683.46431.0665477.492784.4108
27290.019779.52251.0665586.329280.4243
28290.023975.46991.0665687.886776.3258
29290.028071.43451.0665782.113072.2446
30290.034765.04521.0665921.409665.7829
31290.041559.16331.06651.0425e+0359.8342
32290.048253.89051.06651.1469e+0354.5016
33290.055049.23781.06651.2367e+0349.7962
34290.061745.17421.06651.3135e+0345.6865
35290.073939.15281.06651.4251e+0339.5968
36290.086234.59351.06651.5084e+0334.9858
37290.098431.17511.06651.5704e+0331.5286
38290.110628.61741.06651.6167e+0328.9419
39290.122826.70501.06651.6511e+0327.0078
40290.141824.66761.06651.6876e+0324.9473
41290.160923.38631.06651.7106e+0323.6515
42290.179922.57311.06651.7253e+0322.8291
43290.198922.05291.06651.7346e+0322.3030
44290.217921.72181.06651.7404e+0321.9682
45290.248121.44221.06651.7453e+0321.6853
46290.278321.31261.06651.7477e+0321.5543
47290.308421.24441.06651.7490e+0321.4853
48290.338621.20471.06651.7497e+0321.4452
49290.368821.18451.06651.7500e+0321.4248
50290.456821.16801.06651.7502e+0321.4080
51290.544821.17541.06651.7500e+0321.4156
52290.632821.18091.06651.7499e+0321.4211
53290.720821.18041.06651.7500e+0321.4206
54291.165121.17731.06651.7500e+0321.4174
55291.609521.17701.06651.7500e+0321.4171
56292.053821.17711.06651.7500e+0321.4172
57293.053821.17711.06651.7500e+0321.4173
58294.053821.17711.06651.7500e+0321.4173
59295.053821.17711.06651.7500e+0321.4173
60296.053821.17711.06651.7500e+0321.4173
61297.053821.17711.06651.7500e+0321.4173
62298.053821.17711.06651.7500e+0321.4173
63299.053821.17711.06651.7500e+0321.4173
642910.053821.17711.06651.7500e+0321.4173
652911.053821.17711.06651.7500e+0321.4173
662912.053821.17711.06651.7500e+0321.4173
672913.053821.17711.06651.7500e+0321.4173
682914.053821.17711.06651.7500e+0321.4173
692915.053821.17711.06651.7500e+0321.4173
702916.053821.17711.06651.7500e+0321.4173
712917.053821.17711.06651.7500e+0321.4173
722918.053821.17711.06651.7500e+0321.4173
732919.053821.17711.06651.7500e+0321.4173
742920.000021.17711.06651.7500e+0321.4173
752920.000021.17711.06651.7500e+0321.4173
762920.000021.17711.06651.7500e+0321.4173
772921.000021.17071.06681.7497e+0321.4164
782922.000021.16221.06721.7493e+0321.4159
792923.000021.15311.06761.7488e+0321.4157
802924.000021.14381.06811.7482e+0321.4155
812925.000021.13451.06851.7477e+0321.4153
822926.000021.12521.06901.7472e+0321.4152
832927.000021.11591.06951.7467e+0321.4150
842928.000021.10661.06991.7461e+0321.4148
852929.000021.09731.07041.7456e+0321.4147
862930.000021.08811.07081.7451e+0321.4145
872931.000021.07881.07131.7445e+0321.4144
882932.000021.06961.07181.7440e+0321.4142
892933.000021.06031.07221.7435e+0321.4140
902934.000021.05111.07271.7430e+0321.4139
912935.000021.04191.07321.7424e+0321.4137
922936.000021.03271.07361.7419e+0321.4135
932937.000021.02341.07411.7414e+0321.4134
942938.000021.01421.07451.7408e+0321.4132
952939.000021.00511.07501.7403e+0321.4131
962940.000020.99591.07551.7398e+0321.4129
972941.000020.98671.07591.7393e+0321.4127
982942.000020.97751.07641.7387e+0321.4126
992943.000020.96841.07691.7382e+0321.4124
1002944.000020.95921.07731.7377e+0321.4122
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13326×6 table
14356×6 table
15206×6 table
16141×6 table
17238×6 table
18111×6 table
19193×6 table
20581×6 table
21499×6 table
22[ ]
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 176×6 table
 IDtIaIfNT
13092.98721.06659.549399.1687
230.000092.98711.06659.690398.2505
330.000092.98691.06659.829997.4927
430.000092.98671.06659.968396.8706
530.000092.98641.066510.251695.8754
630.000092.98601.066510.532095.2143
730.000092.98571.066510.810594.7877
830.000092.98531.066511.087594.5158
930.000192.98461.066511.613494.2601
1030.000192.98391.066512.138094.1496
1130.000192.98311.066512.662194.0893
1230.000192.98231.066513.186194.0560
1330.000192.98151.066513.709894.0414
1430.000292.97851.066515.398294.0255
1530.000292.97531.066517.086394.0286
1630.000392.97171.066518.774394.0274
1730.000392.96791.066520.462394.0228
1830.000892.91981.066533.772693.9735
1930.001292.85321.066547.070493.9062
2030.001692.76861.066560.352593.8206
2130.003192.36301.0665105.816093.4104
2230.004591.78141.0665150.961092.8223
2330.006091.04301.0665195.683692.0754
2430.007490.16831.0665239.889891.1908
2530.011587.10551.0665361.735688.0933
2630.015683.46431.0665477.492784.4108
2730.019779.52251.0665586.329280.4243
2830.023975.46991.0665687.886776.3258
2930.028071.43451.0665782.113072.2446
3030.034765.04521.0665921.409665.7829
3130.041559.16331.06651.0425e+0359.8342
3230.048253.89051.06651.1469e+0354.5016
3330.055049.23781.06651.2367e+0349.7962
3430.061745.17421.06651.3135e+0345.6865
3530.073939.15281.06651.4251e+0339.5968
3630.086234.59351.06651.5084e+0334.9858
3730.098431.17511.06651.5704e+0331.5286
3830.110628.61741.06651.6167e+0328.9419
3930.122826.70501.06651.6511e+0327.0078
4030.141824.66761.06651.6876e+0324.9473
4130.160923.38631.06651.7106e+0323.6515
4230.179922.57311.06651.7253e+0322.8291
4330.198922.05291.06651.7346e+0322.3030
4430.217921.72181.06651.7404e+0321.9682
4530.248121.44221.06651.7453e+0321.6853
4630.278321.31261.06651.7477e+0321.5543
4730.308421.24441.06651.7490e+0321.4853
4830.338621.20471.06651.7497e+0321.4452
4930.368821.18451.06651.7500e+0321.4248
5030.456821.16801.06651.7502e+0321.4080
5130.544821.17541.06651.7500e+0321.4156
5230.632821.18091.06651.7499e+0321.4211
5330.720821.18041.06651.7500e+0321.4206
5431.165121.17731.06651.7500e+0321.4174
5531.609521.17701.06651.7500e+0321.4171
5632.053821.17711.06651.7500e+0321.4172
5733.053821.17711.06651.7500e+0321.4173
5834.053821.17711.06651.7500e+0321.4173
5935.053821.17711.06651.7500e+0321.4173
6036.053821.17711.06651.7500e+0321.4173
6137.053821.17711.06651.7500e+0321.4173
6238.053821.17711.06651.7500e+0321.4173
6339.053821.17711.06651.7500e+0321.4173
64310.000021.17711.06651.7500e+0321.4173
65310.000021.17711.06651.7500e+0321.4173
66310.000021.17711.06651.7500e+0321.4173
67311.000021.19031.06651.7544e+0321.4306
68312.000021.19141.06651.7591e+0321.4318
69313.000021.19221.06651.7638e+0321.4325
70314.000021.19351.06651.7685e+0321.4338
71315.000021.19491.06651.7732e+0321.4353
72316.000021.19641.06651.7779e+0321.4368
73317.000021.19781.06651.7826e+0321.4382
74318.000021.19931.06651.7873e+0321.4397
75319.000021.20071.06651.7920e+0321.4411
76320.000021.20211.06651.7966e+0321.4426
77321.000021.20361.06651.8013e+0321.4440
78322.000021.20501.06651.8060e+0321.4455
79323.000021.20641.06651.8107e+0321.4469
80324.000021.20791.06651.8154e+0321.4484
81325.000021.20931.06651.8201e+0321.4498
82326.000021.21071.06651.8248e+0321.4513
83327.000021.21221.06651.8294e+0321.4527
84328.000021.21361.06651.8341e+0321.4542
85329.000021.21501.06651.8388e+0321.4556
86330.000021.21651.06651.8435e+0321.4570
87331.000021.21791.06651.8482e+0321.4585
88332.000021.21931.06651.8529e+0321.4599
89333.000021.22071.06651.8576e+0321.4614
90334.000021.22221.06651.8622e+0321.4628
91335.000021.22361.06651.8669e+0321.4643
92336.000021.22501.06651.8716e+0321.4657
93337.000021.22651.06651.8763e+0321.4672
94338.000021.22791.06651.8810e+0321.4686
95339.000021.22931.06651.8857e+0321.4701
96340.000021.23081.06651.8904e+0321.4715
97341.000021.23221.06651.8950e+0321.4730
98342.000021.23361.06651.8997e+0321.4744
99343.000021.23511.06651.9044e+0321.4759
100344.000021.23651.06651.9091e+0321.4773
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13326×6 table
14356×6 table
15206×6 table
16141×6 table
17238×6 table
18111×6 table
19193×6 table
20581×6 table
21499×6 table
22176×6 table
23[ ]
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 281×6 table
 IDtIaIfNT
130092.98721.06659.549399.1687
2300.000092.98711.06659.690398.2505
3300.000092.98691.06659.829997.4927
4300.000092.98671.06659.968396.8706
5300.000092.98641.066510.251695.8754
6300.000092.98601.066510.532095.2143
7300.000092.98571.066510.810594.7877
8300.000092.98531.066511.087594.5158
9300.000192.98461.066511.613494.2601
10300.000192.98391.066512.138094.1496
11300.000192.98311.066512.662194.0893
12300.000192.98231.066513.186194.0560
13300.000192.98151.066513.709894.0414
14300.000292.97851.066515.398294.0255
15300.000292.97531.066517.086394.0286
16300.000392.97171.066518.774394.0274
17300.000392.96791.066520.462394.0228
18300.000892.91981.066533.772693.9735
19300.001292.85321.066547.070493.9062
20300.001692.76861.066560.352593.8206
21300.003192.36301.0665105.816093.4104
22300.004591.78141.0665150.961092.8223
23300.006091.04301.0665195.683692.0754
24300.007490.16831.0665239.889891.1908
25300.011587.10551.0665361.735688.0933
26300.015683.46431.0665477.492784.4108
27300.019779.52251.0665586.329280.4243
28300.023975.46991.0665687.886776.3258
29300.028071.43451.0665782.113072.2446
30300.034765.04521.0665921.409665.7829
31300.041559.16331.06651.0425e+0359.8342
32300.048253.89051.06651.1469e+0354.5016
33300.055049.23781.06651.2367e+0349.7962
34300.061745.17421.06651.3135e+0345.6865
35300.073939.15281.06651.4251e+0339.5968
36300.086234.59351.06651.5084e+0334.9858
37300.098431.17511.06651.5704e+0331.5286
38300.110628.61741.06651.6167e+0328.9419
39300.122826.70501.06651.6511e+0327.0078
40300.141824.66761.06651.6876e+0324.9473
41300.160923.38631.06651.7106e+0323.6515
42300.179922.57311.06651.7253e+0322.8291
43300.198922.05291.06651.7346e+0322.3030
44300.217921.72181.06651.7404e+0321.9682
45300.248121.44221.06651.7453e+0321.6853
46300.278321.31261.06651.7477e+0321.5543
47300.308421.24441.06651.7490e+0321.4853
48300.338621.20471.06651.7497e+0321.4452
49300.368821.18451.06651.7500e+0321.4248
50300.456821.16801.06651.7502e+0321.4080
51300.544821.17541.06651.7500e+0321.4156
52300.632821.18091.06651.7499e+0321.4211
53300.720821.18041.06651.7500e+0321.4206
54301.165121.17731.06651.7500e+0321.4174
55301.609521.17701.06651.7500e+0321.4171
56302.053821.17711.06651.7500e+0321.4172
57303.053821.17711.06651.7500e+0321.4173
58304.053821.17711.06651.7500e+0321.4173
59305.053821.17711.06651.7500e+0321.4173
60306.053821.17711.06651.7500e+0321.4173
61307.053821.17711.06651.7500e+0321.4173
62308.053821.17711.06651.7500e+0321.4173
63309.053821.17711.06651.7500e+0321.4173
643010.053821.17711.06651.7500e+0321.4173
653011.053821.17711.06651.7500e+0321.4173
663012.053821.17711.06651.7500e+0321.4173
673013.053821.17711.06651.7500e+0321.4173
683014.053821.17711.06651.7500e+0321.4173
693015.053821.17711.06651.7500e+0321.4173
703016.053821.17711.06651.7500e+0321.4173
713017.053821.17711.06651.7500e+0321.4173
723018.053821.17711.06651.7500e+0321.4173
733019.053821.17711.06651.7500e+0321.4173
743020.000021.17711.06651.7500e+0321.4173
753020.000021.17711.06651.7500e+0321.4173
763020.000021.17711.06651.7500e+0321.4173
773021.000021.16331.06711.7494e+0321.4153
783022.000021.14491.06801.7484e+0321.4143
793023.000021.12531.06891.7473e+0321.4138
803024.000021.10541.06991.7462e+0321.4134
813025.000021.08551.07091.7450e+0321.4131
823026.000021.06561.07191.7439e+0321.4127
833027.000021.04571.07291.7428e+0321.4124
843028.000021.02581.07391.7416e+0321.4120
853029.000021.00601.07491.7405e+0321.4117
863030.000020.98631.07591.7394e+0321.4113
873031.000020.96651.07691.7382e+0321.4110
883032.000020.94681.07791.7371e+0321.4107
893033.000020.92721.07891.7360e+0321.4103
903034.000020.90751.07991.7348e+0321.4100
913035.000020.88791.08091.7337e+0321.4096
923036.000020.86841.08191.7326e+0321.4093
933037.000020.84891.08281.7315e+0321.4089
943038.000020.82941.08381.7303e+0321.4086
953039.000020.80991.08481.7292e+0321.4082
963040.000020.79051.08581.7281e+0321.4079
973041.000020.77111.08681.7270e+0321.4076
983042.000020.75181.08781.7259e+0321.4072
993043.000020.73251.08881.7247e+0321.4069
1003044.000020.71321.08981.7236e+0321.4065
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13326×6 table
14356×6 table
15206×6 table
16141×6 table
17238×6 table
18111×6 table
19193×6 table
20581×6 table
21499×6 table
22176×6 table
23281×6 table
24[ ]
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 159×6 table
 IDtIaIfNT
131092.98721.06699.549399.2040
2310.000092.98711.06699.690398.2854
3310.000092.98691.06699.830097.5273
4310.000092.98671.06699.968596.9050
5310.000092.98641.066910.251995.9095
6310.000092.98601.066910.532595.2481
7310.000092.98571.066910.811094.8214
8310.000092.98531.066911.088294.5495
9310.000192.98461.066911.614394.2936
10310.000192.98391.066912.139294.1831
11310.000192.98311.066912.663694.1228
12310.000192.98231.066913.187794.0894
13310.000192.98151.066913.711794.0749
14310.000292.97851.066915.400894.0589
15310.000292.97531.066917.089794.0620
16310.000392.97171.066918.778594.0608
17310.000392.96781.066920.467394.0563
18310.000892.91971.066933.783694.0069
19310.001292.85311.066947.087593.9395
20310.001692.76851.066960.375793.8538
21310.003192.36271.0669105.847893.4433
22310.004591.78091.0669151.001392.8547
23310.006091.04211.0669195.732392.1073
24310.007490.16711.0669239.946691.2220
25310.011587.10311.0669361.812388.1222
26310.015683.46051.0669477.586384.4370
27310.019779.51701.0669586.436480.4473
28310.023875.46271.0669688.003976.3456
29310.028071.42551.0669782.236472.2612
30310.034765.03381.0669921.527965.7947
31310.041559.14981.06691.0426e+0359.8418
32310.048253.87531.06691.1470e+0354.5056
33310.054949.22131.06691.2367e+0349.7971
34310.061745.15671.06691.3135e+0345.6850
35310.073939.13581.06691.4250e+0339.5937
36310.086134.57731.06691.5082e+0334.9819
37310.098331.15981.06691.5703e+0331.5243
38310.110628.60311.06691.6165e+0328.9377
39310.122826.69161.06691.6509e+0327.0038
40310.141824.65561.06691.6873e+0324.9441
41310.160823.37551.06691.7103e+0323.6490
42310.179822.56321.06691.7249e+0322.8272
43310.198822.04361.06691.7342e+0322.3015
44310.217821.71301.06691.7400e+0321.9671
45310.247921.43391.06691.7449e+0321.6847
46310.278121.30461.06691.7473e+0321.5538
47310.308321.23661.06691.7485e+0321.4850
48310.338421.19701.06691.7492e+0321.4450
49310.368621.17681.06691.7495e+0321.4246
50310.456621.16031.06691.7498e+0321.4079
51310.544721.16781.06691.7496e+0321.4154
52310.632721.17321.06691.7495e+0321.4210
53310.720721.17281.06691.7495e+0321.4205
54311.165321.16961.06691.7496e+0321.4173
55311.609821.16931.06691.7496e+0321.4170
56312.000021.16941.06691.7496e+0321.4171
57312.000021.16941.06691.7496e+0321.4171
58312.000021.16941.06691.7496e+0321.4171
59312.444521.16991.06691.7497e+0321.4176
60312.889121.17001.06691.7498e+0321.4176
61313.333621.17001.06691.7498e+0321.4177
62313.778221.17001.06691.7499e+0321.4177
63314.778221.17001.06691.7501e+0321.4177
64315.778221.17011.06691.7503e+0321.4178
65316.778221.17021.06691.7505e+0321.4179
66317.778221.17021.06691.7507e+0321.4179
67318.778221.17031.06691.7509e+0321.4180
68319.778221.17031.06691.7511e+0321.4180
693110.778221.17041.06691.7512e+0321.4181
703111.778221.17041.06691.7514e+0321.4181
713112.778221.17051.06691.7516e+0321.4182
723113.778221.17061.06691.7518e+0321.4183
733114.778221.17061.06691.7520e+0321.4183
743115.778221.17071.06691.7522e+0321.4184
753116.778221.17071.06691.7524e+0321.4184
763117.778221.17081.06691.7525e+0321.4185
773118.778221.17091.06691.7527e+0321.4185
783119.778221.17091.06691.7529e+0321.4186
793120.778221.17101.06691.7531e+0321.4187
803121.778221.17101.06691.7533e+0321.4187
813122.778221.17111.06691.7535e+0321.4188
823123.778221.17111.06691.7537e+0321.4188
833124.778221.17121.06691.7539e+0321.4189
843125.778221.17131.06691.7540e+0321.4190
853126.778221.17131.06691.7542e+0321.4190
863127.778221.17141.06691.7544e+0321.4191
873128.778221.17141.06691.7546e+0321.4191
883129.778221.17151.06691.7548e+0321.4192
893130.778221.17151.06691.7550e+0321.4192
903131.778221.17161.06691.7552e+0321.4193
913132.778221.17171.06691.7554e+0321.4194
923133.778221.17171.06691.7555e+0321.4194
933134.778221.17181.06691.7557e+0321.4195
943135.778221.17181.06691.7559e+0321.4195
953136.778221.17191.06691.7561e+0321.4196
963137.778221.17191.06691.7563e+0321.4196
973138.778221.17201.06691.7565e+0321.4197
983139.778221.17211.06691.7567e+0321.4198
993140.778221.17211.06691.7569e+0321.4198
1003141.778221.17221.06691.7570e+0321.4199
⋮
Data = 43×1 cell
 1
1256×6 table
2236×6 table
3226×6 table
4246×6 table
5222×6 table
6207×6 table
7177×6 table
8276×6 table
9271×6 table
10281×6 table
11216×6 table
12226×6 table
13326×6 table
14356×6 table
15206×6 table
16141×6 table
17238×6 table
18111×6 table
19193×6 table
20581×6 table
21499×6 table
22176×6 table
23281×6 table
24159×6 table
25[ ]
26[ ]
27[ ]
28[ ]
29[ ]
30[ ]
31[ ]
32[ ]
33[ ]
34[ ]
35[ ]
36[ ]
37[ ]
38[ ]
39[ ]
40[ ]
41[ ]
42[ ]
43[ ]
t = 159×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 32 0 92.987 1.0669 9.5493 99.204 32 4.2188e-06 92.987 1.0669 9.6903 98.285 32 8.4375e-06 92.987 1.0669 9.83 97.527 32 1.2656e-05 92.987 1.0669 9.9685 96.905 32 2.1367e-05 92.986 1.0669 10.252 95.909 32 3.0077e-05 92.986 1.0669 10.532 95.248 32 3.8787e-05 92.986 1.0669 10.811 94.821 32 4.7497e-05 92.985 1.0669 11.088 94.549 32 6.41e-05 92.985 1.0669 11.614 94.294 32 8.0703e-05 92.984 1.0669 12.139 94.183 32 9.7305e-05 92.983 1.0669 12.664 94.123 32 0.00011391 92.982 1.0669 13.188 94.089 32 0.00013051 92.981 1.0669 13.712 94.075 32 0.00018404 92.979 1.0669 15.401 94.059 32 0.00023757 92.975 1.0669 17.09 94.062 32 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 264×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 33 0 92.987 1.0669 9.5493 99.204 33 4.2188e-06 92.987 1.0669 9.6903 98.285 33 8.4375e-06 92.987 1.0669 9.83 97.527 33 1.2656e-05 92.987 1.0669 9.9685 96.905 33 2.1367e-05 92.986 1.0669 10.252 95.909 33 3.0077e-05 92.986 1.0669 10.532 95.248 33 3.8787e-05 92.986 1.0669 10.811 94.821 33 4.7497e-05 92.985 1.0669 11.088 94.549 33 6.41e-05 92.985 1.0669 11.614 94.294 33 8.0703e-05 92.984 1.0669 12.139 94.183 33 9.7305e-05 92.983 1.0669 12.664 94.123 33 0.00011391 92.982 1.0669 13.188 94.089 33 0.00013051 92.981 1.0669 13.712 94.075 33 0.00018404 92.979 1.0669 15.401 94.059 33 0.00023757 92.975 1.0669 17.09 94.062 33 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 265×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 34 0 92.987 1.0669 9.5493 99.204 34 4.2188e-06 92.987 1.0669 9.6903 98.285 34 8.4375e-06 92.987 1.0669 9.83 97.527 34 1.2656e-05 92.987 1.0669 9.9685 96.905 34 2.1367e-05 92.986 1.0669 10.252 95.909 34 3.0077e-05 92.986 1.0669 10.532 95.248 34 3.8787e-05 92.986 1.0669 10.811 94.821 34 4.7497e-05 92.985 1.0669 11.088 94.549 34 6.41e-05 92.985 1.0669 11.614 94.294 34 8.0703e-05 92.984 1.0669 12.139 94.183 34 9.7305e-05 92.983 1.0669 12.664 94.123 34 0.00011391 92.982 1.0669 13.188 94.089 34 0.00013051 92.981 1.0669 13.712 94.075 34 0.00018404 92.979 1.0669 15.401 94.059 34 0.00023757 92.975 1.0669 17.09 94.062 34 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 146×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 35 0 92.987 1.0669 9.5493 99.204 35 4.2188e-06 92.987 1.0669 9.6903 98.285 35 8.4375e-06 92.987 1.0669 9.83 97.527 35 1.2656e-05 92.987 1.0669 9.9685 96.905 35 2.1367e-05 92.986 1.0669 10.252 95.909 35 3.0077e-05 92.986 1.0669 10.532 95.248 35 3.8787e-05 92.986 1.0669 10.811 94.821 35 4.7497e-05 92.985 1.0669 11.088 94.549 35 6.41e-05 92.985 1.0669 11.614 94.294 35 8.0703e-05 92.984 1.0669 12.139 94.183 35 9.7305e-05 92.983 1.0669 12.664 94.123 35 0.00011391 92.982 1.0669 13.188 94.089 35 0.00013051 92.981 1.0669 13.712 94.075 35 0.00018404 92.979 1.0669 15.401 94.059 35 0.00023757 92.975 1.0669 17.09 94.062 35 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 146×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 36 0 92.987 1.0669 9.5493 99.204 36 4.2188e-06 92.987 1.0669 9.6903 98.285 36 8.4375e-06 92.987 1.0669 9.83 97.527 36 1.2656e-05 92.987 1.0669 9.9685 96.905 36 2.1367e-05 92.986 1.0669 10.252 95.909 36 3.0077e-05 92.986 1.0669 10.532 95.248 36 3.8787e-05 92.986 1.0669 10.811 94.821 36 4.7497e-05 92.985 1.0669 11.088 94.549 36 6.41e-05 92.985 1.0669 11.614 94.294 36 8.0703e-05 92.984 1.0669 12.139 94.183 36 9.7305e-05 92.983 1.0669 12.664 94.123 36 0.00011391 92.982 1.0669 13.188 94.089 36 0.00013051 92.981 1.0669 13.712 94.075 36 0.00018404 92.979 1.0669 15.401 94.059 36 0.00023757 92.975 1.0669 17.09 94.062 36 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 206×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 37 0 92.987 1.0669 9.5493 99.204 37 4.2188e-06 92.987 1.0669 9.6903 98.285 37 8.4375e-06 92.987 1.0669 9.83 97.527 37 1.2656e-05 92.987 1.0669 9.9685 96.905 37 2.1367e-05 92.986 1.0669 10.252 95.909 37 3.0077e-05 92.986 1.0669 10.532 95.248 37 3.8787e-05 92.986 1.0669 10.811 94.821 37 4.7497e-05 92.985 1.0669 11.088 94.549 37 6.41e-05 92.985 1.0669 11.614 94.294 37 8.0703e-05 92.984 1.0669 12.139 94.183 37 9.7305e-05 92.983 1.0669 12.664 94.123 37 0.00011391 92.982 1.0669 13.188 94.089 37 0.00013051 92.981 1.0669 13.712 94.075 37 0.00018404 92.979 1.0669 15.401 94.059 37 0.00023757 92.975 1.0669 17.09 94.062 37 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 256×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 38 0 92.987 1.0669 9.5493 99.204 38 4.2188e-06 92.987 1.0669 9.6903 98.285 38 8.4375e-06 92.987 1.0669 9.83 97.527 38 1.2656e-05 92.987 1.0669 9.9685 96.905 38 2.1367e-05 92.986 1.0669 10.252 95.909 38 3.0077e-05 92.986 1.0669 10.532 95.248 38 3.8787e-05 92.986 1.0669 10.811 94.821 38 4.7497e-05 92.985 1.0669 11.088 94.549 38 6.41e-05 92.985 1.0669 11.614 94.294 38 8.0703e-05 92.984 1.0669 12.139 94.183 38 9.7305e-05 92.983 1.0669 12.664 94.123 38 0.00011391 92.982 1.0669 13.188 94.089 38 0.00013051 92.981 1.0669 13.712 94.075 38 0.00018404 92.979 1.0669 15.401 94.059 38 0.00023757 92.975 1.0669 17.09 94.062 38 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 256×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 39 0 92.987 1.0669 9.5493 99.204 39 4.2188e-06 92.987 1.0669 9.6903 98.285 39 8.4375e-06 92.987 1.0669 9.83 97.527 39 1.2656e-05 92.987 1.0669 9.9685 96.905 39 2.1367e-05 92.986 1.0669 10.252 95.909 39 3.0077e-05 92.986 1.0669 10.532 95.248 39 3.8787e-05 92.986 1.0669 10.811 94.821 39 4.7497e-05 92.985 1.0669 11.088 94.549 39 6.41e-05 92.985 1.0669 11.614 94.294 39 8.0703e-05 92.984 1.0669 12.139 94.183 39 9.7305e-05 92.983 1.0669 12.664 94.123 39 0.00011391 92.982 1.0669 13.188 94.089 39 0.00013051 92.981 1.0669 13.712 94.075 39 0.00018404 92.979 1.0669 15.401 94.059 39 0.00023757 92.975 1.0669 17.09 94.062 39 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 137×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 4 0 92.987 1.0665 9.5493 99.169 4 4.2188e-06 92.987 1.0665 9.6903 98.251 4 8.4375e-06 92.987 1.0665 9.8299 97.493 4 1.2656e-05 92.987 1.0665 9.9683 96.871 4 2.1367e-05 92.986 1.0665 10.252 95.875 4 3.0077e-05 92.986 1.0665 10.532 95.214 4 3.8787e-05 92.986 1.0665 10.81 94.788 4 4.7497e-05 92.985 1.0665 11.088 94.516 4 6.41e-05 92.985 1.0665 11.613 94.26 4 8.0703e-05 92.984 1.0665 12.138 94.15 4 9.7305e-05 92.983 1.0665 12.662 94.089 4 0.00011391 92.982 1.0665 13.186 94.056 4 0.00013051 92.981 1.0665 13.71 94.041 4 0.00018404 92.979 1.0665 15.398 94.025 4 0.00023757 92.975 1.0665 17.086 94.029 4 0.0002911 92.972 1.0665 18.774 94.027
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 156×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 40 0 92.987 1.0669 9.5493 99.204 40 4.2188e-06 92.987 1.0669 9.6903 98.285 40 8.4375e-06 92.987 1.0669 9.83 97.527 40 1.2656e-05 92.987 1.0669 9.9685 96.905 40 2.1367e-05 92.986 1.0669 10.252 95.909 40 3.0077e-05 92.986 1.0669 10.532 95.248 40 3.8787e-05 92.986 1.0669 10.811 94.821 40 4.7497e-05 92.985 1.0669 11.088 94.549 40 6.41e-05 92.985 1.0669 11.614 94.294 40 8.0703e-05 92.984 1.0669 12.139 94.183 40 9.7305e-05 92.983 1.0669 12.664 94.123 40 0.00011391 92.982 1.0669 13.188 94.089 40 0.00013051 92.981 1.0669 13.712 94.075 40 0.00018404 92.979 1.0669 15.401 94.059 40 0.00023757 92.975 1.0669 17.09 94.062 40 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 159×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 41 0 92.987 1.0669 9.5493 99.204 41 4.2188e-06 92.987 1.0669 9.6903 98.285 41 8.4375e-06 92.987 1.0669 9.83 97.527 41 1.2656e-05 92.987 1.0669 9.9685 96.905 41 2.1367e-05 92.986 1.0669 10.252 95.909 41 3.0077e-05 92.986 1.0669 10.532 95.248 41 3.8787e-05 92.986 1.0669 10.811 94.821 41 4.7497e-05 92.985 1.0669 11.088 94.549 41 6.41e-05 92.985 1.0669 11.614 94.294 41 8.0703e-05 92.984 1.0669 12.139 94.183 41 9.7305e-05 92.983 1.0669 12.664 94.123 41 0.00011391 92.982 1.0669 13.188 94.089 41 0.00013051 92.981 1.0669 13.712 94.075 41 0.00018404 92.979 1.0669 15.401 94.059 41 0.00023757 92.975 1.0669 17.09 94.062 41 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 206×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 42 0 92.987 1.0669 9.5493 99.204 42 4.2188e-06 92.987 1.0669 9.6903 98.285 42 8.4375e-06 92.987 1.0669 9.83 97.527 42 1.2656e-05 92.987 1.0669 9.9685 96.905 42 2.1367e-05 92.986 1.0669 10.252 95.909 42 3.0077e-05 92.986 1.0669 10.532 95.248 42 3.8787e-05 92.986 1.0669 10.811 94.821 42 4.7497e-05 92.985 1.0669 11.088 94.549 42 6.41e-05 92.985 1.0669 11.614 94.294 42 8.0703e-05 92.984 1.0669 12.139 94.183 42 9.7305e-05 92.983 1.0669 12.664 94.123 42 0.00011391 92.982 1.0669 13.188 94.089 42 0.00013051 92.981 1.0669 13.712 94.075 42 0.00018404 92.979 1.0669 15.401 94.059 42 0.00023757 92.975 1.0669 17.09 94.062 42 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 116×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 43 0 92.987 1.0669 9.5493 99.204 43 4.2188e-06 92.987 1.0669 9.6903 98.285 43 8.4375e-06 92.987 1.0669 9.83 97.527 43 1.2656e-05 92.987 1.0669 9.9685 96.905 43 2.1367e-05 92.986 1.0669 10.252 95.909 43 3.0077e-05 92.986 1.0669 10.532 95.248 43 3.8787e-05 92.986 1.0669 10.811 94.821 43 4.7497e-05 92.985 1.0669 11.088 94.549 43 6.41e-05 92.985 1.0669 11.614 94.294 43 8.0703e-05 92.984 1.0669 12.139 94.183 43 9.7305e-05 92.983 1.0669 12.664 94.123 43 0.00011391 92.982 1.0669 13.188 94.089 43 0.00013051 92.981 1.0669 13.712 94.075 43 0.00018404 92.979 1.0669 15.401 94.059 43 0.00023757 92.975 1.0669 17.09 94.062 43 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 213×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 44 0 92.987 1.0669 9.5493 99.204 44 4.2188e-06 92.987 1.0669 9.6903 98.285 44 8.4375e-06 92.987 1.0669 9.83 97.527 44 1.2656e-05 92.987 1.0669 9.9685 96.905 44 2.1367e-05 92.986 1.0669 10.252 95.909 44 3.0077e-05 92.986 1.0669 10.532 95.248 44 3.8787e-05 92.986 1.0669 10.811 94.821 44 4.7497e-05 92.985 1.0669 11.088 94.549 44 6.41e-05 92.985 1.0669 11.614 94.294 44 8.0703e-05 92.984 1.0669 12.139 94.183 44 9.7305e-05 92.983 1.0669 12.664 94.123 44 0.00011391 92.982 1.0669 13.188 94.089 44 0.00013051 92.981 1.0669 13.712 94.075 44 0.00018404 92.979 1.0669 15.401 94.059 44 0.00023757 92.975 1.0669 17.09 94.062 44 0.0002911 92.972 1.0669 18.779 94.061
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 132×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 5 0 92.987 1.0665 9.5493 99.169 5 4.2188e-06 92.987 1.0665 9.6903 98.251 5 8.4375e-06 92.987 1.0665 9.8299 97.493 5 1.2656e-05 92.987 1.0665 9.9683 96.871 5 2.1367e-05 92.986 1.0665 10.252 95.875 5 3.0077e-05 92.986 1.0665 10.532 95.214 5 3.8787e-05 92.986 1.0665 10.81 94.788 5 4.7497e-05 92.985 1.0665 11.088 94.516 5 6.41e-05 92.985 1.0665 11.613 94.26 5 8.0703e-05 92.984 1.0665 12.138 94.15 5 9.7305e-05 92.983 1.0665 12.662 94.089 5 0.00011391 92.982 1.0665 13.186 94.056 5 0.00013051 92.981 1.0665 13.71 94.041 5 0.00018404 92.979 1.0665 15.398 94.025 5 0.00023757 92.975 1.0665 17.086 94.029 5 0.0002911 92.972 1.0665 18.774 94.027
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 129×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 6 0 92.987 1.0665 9.5493 99.169 6 4.2188e-06 92.987 1.0665 9.6903 98.251 6 8.4375e-06 92.987 1.0665 9.8299 97.493 6 1.2656e-05 92.987 1.0665 9.9683 96.871 6 2.1367e-05 92.986 1.0665 10.252 95.875 6 3.0077e-05 92.986 1.0665 10.532 95.214 6 3.8787e-05 92.986 1.0665 10.81 94.788 6 4.7497e-05 92.985 1.0665 11.088 94.516 6 6.41e-05 92.985 1.0665 11.613 94.26 6 8.0703e-05 92.984 1.0665 12.138 94.15 6 9.7305e-05 92.983 1.0665 12.662 94.089 6 0.00011391 92.982 1.0665 13.186 94.056 6 0.00013051 92.981 1.0665 13.71 94.041 6 0.00018404 92.979 1.0665 15.398 94.025 6 0.00023757 92.975 1.0665 17.086 94.029 6 0.0002911 92.972 1.0665 18.774 94.027
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 156×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 7 0 92.987 1.0665 9.5493 99.169 7 4.2188e-06 92.987 1.0665 9.6903 98.251 7 8.4375e-06 92.987 1.0665 9.8299 97.493 7 1.2656e-05 92.987 1.0665 9.9683 96.871 7 2.1367e-05 92.986 1.0665 10.252 95.875 7 3.0077e-05 92.986 1.0665 10.532 95.214 7 3.8787e-05 92.986 1.0665 10.81 94.788 7 4.7497e-05 92.985 1.0665 11.088 94.516 7 6.41e-05 92.985 1.0665 11.613 94.26 7 8.0703e-05 92.984 1.0665 12.138 94.15 7 9.7305e-05 92.983 1.0665 12.662 94.089 7 0.00011391 92.982 1.0665 13.186 94.056 7 0.00013051 92.981 1.0665 13.71 94.041 7 0.00018404 92.979 1.0665 15.398 94.025 7 0.00023757 92.975 1.0665 17.086 94.029 7 0.0002911 92.972 1.0665 18.774 94.027
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 241×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 8 0 92.987 1.0665 9.5493 99.169 8 4.2188e-06 92.987 1.0665 9.6903 98.251 8 8.4375e-06 92.987 1.0665 9.8299 97.493 8 1.2656e-05 92.987 1.0665 9.9683 96.871 8 2.1367e-05 92.986 1.0665 10.252 95.875 8 3.0077e-05 92.986 1.0665 10.532 95.214 8 3.8787e-05 92.986 1.0665 10.81 94.788 8 4.7497e-05 92.985 1.0665 11.088 94.516 8 6.41e-05 92.985 1.0665 11.613 94.26 8 8.0703e-05 92.984 1.0665 12.138 94.15 8 9.7305e-05 92.983 1.0665 12.662 94.089 8 0.00011391 92.982 1.0665 13.186 94.056 8 0.00013051 92.981 1.0665 13.71 94.041 8 0.00018404 92.979 1.0665 15.398 94.025 8 0.00023757 92.975 1.0665 17.086 94.029 8 0.0002911 92.972 1.0665 18.774 94.027
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
t = 246×6 table
ID t Ia If N T __ __________ ______ ______ ______ ______ 9 0 92.987 1.0665 9.5493 99.169 9 4.2188e-06 92.987 1.0665 9.6903 98.251 9 8.4375e-06 92.987 1.0665 9.8299 97.493 9 1.2656e-05 92.987 1.0665 9.9683 96.871 9 2.1367e-05 92.986 1.0665 10.252 95.875 9 3.0077e-05 92.986 1.0665 10.532 95.214 9 3.8787e-05 92.986 1.0665 10.81 94.788 9 4.7497e-05 92.985 1.0665 11.088 94.516 9 6.41e-05 92.985 1.0665 11.613 94.26 9 8.0703e-05 92.984 1.0665 12.138 94.15 9 9.7305e-05 92.983 1.0665 12.662 94.089 9 0.00011391 92.982 1.0665 13.186 94.056 9 0.00013051 92.981 1.0665 13.71 94.041 9 0.00018404 92.979 1.0665 15.398 94.025 9 0.00023757 92.975 1.0665 17.086 94.029 9 0.0002911 92.972 1.0665 18.774 94.027
Data = 43×1 cell array
{256×6 table} {236×6 table} {226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {276×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table}
Data is the cell array through which every simulation can be iterated. We do have different types of data
variables like ‘T’, ‘N’, ‘Ia’, ‘If’ and one time variable as ‘t’ and one ‘ID’ variable which is not of much use. I have
divided these variables into different categories from the code given below.
varNames = string(Data{1}.Properties.VariableNames);
timeVariable = varNames{2};
dataVariables = varNames(3:6);
We do have total 43 simulations so we need to divide the given data into train data and validation data. I do
have taken numfold in such a way that train data contains 38 instances and validation data contains only five
instances. Rng is set to default to make the results repeatable.
rng('default') %Control random number generator a
numEnsemble = length(Data);
numFold = 8;
cv = cvpartition(numEnsemble, 'KFold', numFold); %Partition data for cross-validation
trainData = Data(training(cv, 1));
validationData = Data(test(cv, 1));
nsample = 20;
figure
helperPlotEnsemble(trainData, timeVariable, ...
dataVariables(1:4), nsample)
As our data do not contain multiple operating conditions it is not needed to do clustering, as we have used the same machine with different inputs for introducing faults. I do have normalised the data, I am not sure what is the need of this step. But it usually helps in machine learning algorithms as if,As an example, Field current is having a range in in 0-5A and ‘torque’ in range 0-1000Nm so due to this difference in range it creates problems in training a model. More preference will be given to torque which should not be the case. Therefore whole data is normalised wrt train data. Code is given below:
First mean and standard deviation is found by concatenating whole training data.
trainDataUnwrap = vertcat(trainData{:}); %vertcat = Concatenate arrays vertically
centerstats = struct('Mean', table(), 'SD', table());
for v = dataVariables
centerstats.Mean.(char(v)) = splitapply(@mean, trainDataUnwrap.(char(v)),1 );
centerstats.SD.(char(v)) = splitapply(@std, trainDataUnwrap.(char(v)), 1);
end
centerstats
centerstats = struct with fields:
Mean: [1×4 table] SD: [1×4 table]
centerstats.Mean
ans = 1×4 table
Ia If N T ______ ______ ______ ______ 30.459 1.1241 2033.8 31.659
centerstats.SD
ans = 1×4 table
Ia If N T ______ _______ ____ ______ 23.751 0.23276 3241 23.871
Now whole train data is normalised into new variable new_train:
new_train=trainData
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
for i=1:numel(trainData)
new_train{i}.Ia=(trainData{i}.Ia-centerstats.Mean.Ia)/centerstats.SD.Ia
new_train{i}.If=(trainData{i}.If-centerstats.Mean.If)/centerstats.SD.If
new_train{i}.N=(trainData{i}.N-centerstats.Mean.N)/centerstats.SD.N
new_train{i}.T=(trainData{i}.T-centerstats.Mean.T)/centerstats.SD.T
end
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
new_train = 38×1 cell array
{226×6 table} {246×6 table} {222×6 table} {207×6 table} {177×6 table} {271×6 table} {281×6 table} {216×6 table} {226×6 table} {326×6 table} {356×6 table} {206×6 table} {141×6 table} {238×6 table} {111×6 table} {581×6 table}
Full training data and new_train data is plotted with the help of helperplot function into two different figures from similarity model based approach, you have to just put the premade function into your working directory. Or just double click on the error it will do the whole thing on its own.
%Real Train Data Plot
nsample = 38;
figure
helperPlotEnsemble(trainData, timeVariable, ...
[dataVariables(1:4)], nsample)
%normalised train data plot
nsample = 38;
figure
helperPlotEnsemble(new_train, timeVariable, ...
[dataVariables(1:4)], nsample)
As we do have only four sensor measurements “Ia”, “If”, “N”, and “T” so we do not need to take out only those measurements which do have positive or negative trend. Like as an example if we do have 26 sensor measurements as in reference model we can take out 8-10 most important features which are undergoing changes as machine goes from healthy state to faulty state.
But for the sake of convenience I have used Linear degradation model which can sort the slope of variables in whole train data from which most trendable can be choosed. Here is the code:
numSensors = length(dataVariables);
signalSlope = zeros(numSensors, 1);
warn = warning('off');
for ct = 1:numSensors
tmp = cellfun(@(tbl) tbl(:, cellstr(dataVariables(ct))), new_train, 'UniformOutput', false);
mdl = linearDegradationModel(); % create model
fit(mdl, tmp); % train mode
signalSlope(ct) = mdl.Theta;
end
warning(warn);
[~, idx] = sort(abs(signalSlope), 'descend');
figure
helperPlotEnsemble(new_train, timeVariable, dataVariables(idx), nsample)
Variables has been plot in the order of their slope. But I think it will be of not much use in our model reason as we do have very less no of variables, reducing them does not make sense.
Now in upcoming time we will construct health indicator which will go from healthy state to faulty i.e.. 1 to 0. It is just needed to fuse whole training data into one variable it will help in taking less complex machine learning algorithms.
for j=1:numel(new_train)
dataset = new_train{j};
rul = max(dataset.t)-dataset.t;
dataset.health_condition = rul / max(rul);
new_train{j} = dataset;
end
Now this health condition is plotted for new_train(normalised train data):
figure
helperPlotEnsemble(new_train, timeVariable, "health_condition", nsample)
newtrainUnwrap = vertcat(new_train{:});
sensorToFuse = dataVariables(idx);
X = newtrainUnwrap{:, cellstr(sensorToFuse)};
y = newtrainUnwrap.health_condition;
// whole data is now fit into linear regression model means they are basically trying to find the health indicator in form of four variables in linear form, for which there will be slope for each variable and a bias term. It will be helpful in further process.
regModel = fitlm(X,y)
regModel =
Linear regression model: y ~ 1 + x1 + x2 + x3 + x4 Estimated Coefficients: Estimate SE tStat pValue ________ _________ _______ ___________ (Intercept) 0.62091 0.002779 223.43 0 x1 2.5238 0.073019 34.563 2.9204e-245 x2 -2.3637 0.072413 -32.641 1.905e-220 x3 -0.07245 0.0028551 -25.376 4.6401e-137 x4 0.088752 0.0054967 16.146 8.4691e-58 Number of observations: 8619, Error degrees of freedom: 8614 Root Mean Squared Error: 0.258 R-squared: 0.39, Adjusted R-Squared: 0.389 F-statistic vs. constant model: 1.38e+03, p-value = 0
bias = regModel.Coefficients.Estimate(1)
bias = 0.6209
weights = regModel.Coefficients.Estimate(2:end)
weights = 4×1
2.5238 -2.3637 -0.0725 0.0888
Construct a single health indicator by multiplying the sensor measurements with their associated weights .
trainDataFused=cell(38,1)
trainDataFused = 38×1 cell array
{0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double}
for j=1:numel(new_train)
data=new_train{j}
datatofuse=data{:,cellstr(sensorToFuse)};
dataFuseRaw=datatofuse*weights;
trainDataFused{j}=dataFuseRaw;
disp(j)
end
data = 226×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 11 0 2.6327 -0.24773 -0.62456 2.8281 1 11 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 11 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 11 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 11 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 11 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 11 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 11 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 11 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 11 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 11 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 11 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 11 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 11 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 11 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 11 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
1
data = 246×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 12 0 2.6327 -0.24773 -0.62456 2.8281 1 12 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 12 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 12 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 12 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 12 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 12 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 12 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 12 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 12 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 12 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 12 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 12 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 12 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 12 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 12 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
2
data = 222×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 13 0 2.6327 -0.24773 -0.62456 2.8281 1 13 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 13 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 13 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 13 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 13 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 13 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 13 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 13 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 13 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 13 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 13 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 13 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 13 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 13 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 13 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
3
data = 207×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 14 0 2.6327 -0.24773 -0.62456 2.8281 1 14 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 14 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 14 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 14 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 14 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 14 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 14 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 14 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 14 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 14 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 14 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 14 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 14 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 14 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 14 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
4
data = 177×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 15 0 2.6327 -0.24773 -0.62456 2.8281 1 15 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 15 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 15 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 15 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 15 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 15 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 15 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 15 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 15 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 15 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 15 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 15 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 15 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 15 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 15 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
5
data = 271×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 17 0 2.6327 -0.24773 -0.62456 2.8281 1 17 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 17 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 17 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 17 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 17 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 17 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 17 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 17 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 17 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 17 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 17 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 17 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 17 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 17 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 17 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
6
data = 281×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 18 0 2.6327 -0.24773 -0.62456 2.8281 1 18 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 18 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 18 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 18 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 18 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 18 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 18 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 18 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 18 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 18 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 18 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 18 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 18 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 18 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 18 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
7
data = 216×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 19 0 2.6327 -0.24773 -0.62456 2.8281 1 19 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 19 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 19 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 19 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 19 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 19 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 19 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 19 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 19 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 19 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 19 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 19 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 19 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 19 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 19 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
8
data = 226×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 2 0 2.6327 -0.24773 -0.62456 2.8281 1 2 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 2 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 2 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 2 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 2 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 2 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 2 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 2 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 2 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 2 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 2 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 2 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 2 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 2 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 2 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
9
data = 326×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 20 0 2.6327 -0.24773 -0.62456 2.8281 1 20 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 20 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 20 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 20 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 20 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 20 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 20 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 20 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 20 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 20 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 20 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 20 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 20 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 20 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 20 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
10
data = 356×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 21 0 2.6327 -0.24773 -0.62456 2.8281 1 21 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 21 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 21 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 21 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 21 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 21 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 21 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 21 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 21 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 21 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 21 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 21 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 21 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 21 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 21 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
11
data = 206×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 22 0 2.6327 -0.24773 -0.62456 2.8281 1 22 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 22 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 22 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 22 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 22 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 22 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 22 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 22 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 22 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 22 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 22 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 22 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 22 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 22 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 22 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
12
data = 141×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 23 0 2.6327 -0.24773 -0.62456 2.8281 1 23 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 23 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 23 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 23 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 23 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 23 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 23 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 23 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 23 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 23 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 23 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 23 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 23 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 23 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 23 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
13
data = 238×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 25 0 2.6327 -0.24773 -0.62456 2.8281 1 25 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 25 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 25 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 25 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 25 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 25 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 25 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 25 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 25 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 25 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 25 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 25 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 25 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 25 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 25 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
14
data = 111×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 26 0 2.6327 -0.24773 -0.62456 2.8281 1 26 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 26 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 26 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 26 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 26 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 26 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 26 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 26 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 26 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 26 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 26 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 26 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 26 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 26 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 26 0.0002911 2.632 -0.24773 -0.62172 2.6127 0.99999
15
data = 581×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 28 0 2.6327 -0.24773 -0.62456 2.8281 1 28 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 28 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 28 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 28 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 28 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 28 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 28 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 28 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 28 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 28 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 28 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 28 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 28 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 28 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 28 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
16
data = 499×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 29 0 2.6327 -0.24773 -0.62456 2.8281 1 29 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 29 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 29 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 29 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 29 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 29 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 29 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 29 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 29 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 29 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 29 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 29 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 29 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 29 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 29 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
17
data = 176×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 3 0 2.6327 -0.24773 -0.62456 2.8281 1 3 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 3 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 3 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 3 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 3 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 3 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 3 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 3 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 3 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 3 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 3 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 3 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 3 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 3 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 3 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
18
data = 281×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 30 0 2.6327 -0.24773 -0.62456 2.8281 1 30 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 30 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 30 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 30 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 30 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 30 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 30 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 30 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 30 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 30 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 30 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 30 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 30 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 30 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 30 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
19
data = 159×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 31 0 2.6327 -0.2461 -0.62456 2.8296 1 31 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 31 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 31 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 31 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 31 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 31 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 31 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 31 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 31 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 31 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 31 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 31 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 31 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 31 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 31 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
20
data = 159×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 32 0 2.6327 -0.2461 -0.62456 2.8296 1 32 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 32 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 32 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 32 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 32 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 32 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 32 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 32 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 32 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 32 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 32 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 32 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 32 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 32 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 32 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
21
data = 264×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 33 0 2.6327 -0.2461 -0.62456 2.8296 1 33 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 33 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 33 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 33 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 33 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 33 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 33 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 33 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 33 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 33 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 33 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 33 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 33 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 33 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 33 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
22
data = 265×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 34 0 2.6327 -0.2461 -0.62456 2.8296 1 34 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 34 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 34 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 34 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 34 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 34 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 34 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 34 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 34 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 34 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 34 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 34 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 34 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 34 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 34 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
23
data = 146×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 35 0 2.6327 -0.2461 -0.62456 2.8296 1 35 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 35 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 35 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 35 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 35 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 35 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 35 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 35 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 35 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 35 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 35 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 35 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 35 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 35 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 35 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
24
data = 146×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 36 0 2.6327 -0.2461 -0.62456 2.8296 1 36 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 36 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 36 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 36 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 36 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 36 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 36 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 36 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 36 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 36 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 36 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 36 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 36 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 36 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 36 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
25
data = 206×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 37 0 2.6327 -0.2461 -0.62456 2.8296 1 37 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 37 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 37 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 37 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 37 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 37 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 37 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 37 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 37 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 37 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 37 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 37 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 37 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 37 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 37 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
26
data = 256×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 38 0 2.6327 -0.2461 -0.62456 2.8296 1 38 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 38 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 38 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 38 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 38 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 38 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 38 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 38 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 38 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 38 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 38 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 38 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 38 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 38 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 38 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
27
data = 256×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 39 0 2.6327 -0.2461 -0.62456 2.8296 1 39 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 39 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 39 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 39 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 39 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 39 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 39 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 39 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 39 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 39 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 39 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 39 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 39 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 39 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 39 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
28
data = 137×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 4 0 2.6327 -0.24773 -0.62456 2.8281 1 4 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 4 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 4 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 4 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 4 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 4 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 4 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 4 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 4 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 4 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 4 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 4 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 4 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 4 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 4 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
29
data = 156×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 40 0 2.6327 -0.2461 -0.62456 2.8296 1 40 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 40 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 40 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 40 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 40 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 40 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 40 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 40 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 40 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 40 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 40 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 40 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 40 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 40 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 40 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
30
data = 159×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 41 0 2.6327 -0.2461 -0.62456 2.8296 1 41 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 41 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 41 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 41 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 41 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 41 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 41 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 41 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 41 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 41 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 41 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 41 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 41 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 41 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 41 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
31
data = 206×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 42 0 2.6327 -0.2461 -0.62456 2.8296 1 42 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 42 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 42 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 42 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 42 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 42 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 42 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 42 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 42 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 42 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 42 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 42 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 42 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 42 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 42 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
32
data = 213×7 table
ID t Ia If N T health_condition __ __________ ______ _______ ________ ______ ________________ 44 0 2.6327 -0.2461 -0.62456 2.8296 1 44 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 1 44 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 1 44 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 1 44 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 1 44 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 1 44 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 1 44 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 1 44 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 1 44 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 1 44 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 1 44 0.00011391 2.6325 -0.2461 -0.62344 2.6153 1 44 0.00013051 2.6325 -0.2461 -0.62328 2.6147 1 44 0.00018404 2.6323 -0.2461 -0.62276 2.614 1 44 0.00023757 2.6322 -0.2461 -0.62224 2.6142 1 44 0.0002911 2.632 -0.2461 -0.62171 2.6141 1
33
data = 132×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 5 0 2.6327 -0.24773 -0.62456 2.8281 1 5 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 5 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 5 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 5 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 5 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 5 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 5 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 5 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 5 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 5 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 5 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 5 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 5 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 5 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 5 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
34
data = 129×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 6 0 2.6327 -0.24773 -0.62456 2.8281 1 6 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 6 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 6 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 6 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 6 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 6 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 6 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 6 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 6 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 6 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 6 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 6 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 6 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 6 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 6 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
35
data = 156×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 7 0 2.6327 -0.24773 -0.62456 2.8281 1 7 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 7 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 7 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 7 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 7 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 7 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 7 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 7 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 7 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 7 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 7 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 7 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 7 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 7 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 7 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
36
data = 241×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 8 0 2.6327 -0.24773 -0.62456 2.8281 1 8 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 8 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 8 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 8 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 8 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 8 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 8 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 8 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 8 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 8 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 8 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 8 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 8 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 8 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 8 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
37
data = 246×7 table
ID t Ia If N T health_condition __ __________ ______ ________ ________ ______ ________________ 9 0 2.6327 -0.24773 -0.62456 2.8281 1 9 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 9 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 9 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 9 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 9 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 9 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 9 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 9 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 9 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 9 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 9 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 9 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 9 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 9 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 9 0.0002911 2.632 -0.24773 -0.62172 2.6127 1
38
figure
helperPlotEnsemble(trainDataFused, [], 1, 14)
xlabel('Time')
ylabel('Health Indicator')
title('Training Data')
Process of removing outliers does not work so we need to do some alternative thing, let it be just doing the things that were done in the tutorial and make necessary changes afterwards.
Repeat the normalisation step on the validation data using the same mean and std deviation. Then all those variables are also added in the same way as training data using the same weights.
validationDataNormalized=validationData
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
for i=1:numel(validationData)
validationDataNormalized{i}.Ia=(validationData{i}.Ia-centerstats.Mean.Ia)/centerstats.SD.Ia
validationDataNormalized{i}.If=(validationData{i}.If-centerstats.Mean.If)/centerstats.SD.If
validationDataNormalized{i}.N=(validationData{i}.N-centerstats.Mean.N)/centerstats.SD.N
validationDataNormalized{i}.T=(validationData{i}.T-centerstats.Mean.T)/centerstats.SD.T
end
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationDataNormalized = 5×1 cell array
{256×6 table} {236×6 table} {276×6 table} {193×6 table} {116×6 table}
validationdatafused=cell(5,1)
validationdatafused = 5×1 cell array
{0×0 double} {0×0 double} {0×0 double} {0×0 double} {0×0 double}
for j=1:numel(validationDataNormalized)
data=validationDataNormalized{j}
datatofuse=data{:,cellstr(sensorToFuse)};
dataFuseRaw=datatofuse*weights;
validationdatafused{j}=dataFuseRaw;
disp(j)
end
data = 256×6 table
ID t Ia If N T __ __________ ______ ________ ________ ______ 1 0 2.6327 -0.24773 -0.62456 2.8281 1 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 1 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 1 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 1 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 1 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 1 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 1 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 1 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 1 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 1 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 1 0.00011391 2.6325 -0.24773 -0.62344 2.6139 1 0.00013051 2.6325 -0.24773 -0.62328 2.6133 1 0.00018404 2.6323 -0.24773 -0.62276 2.6126 1 0.00023757 2.6322 -0.24773 -0.62224 2.6128 1 0.0002911 2.632 -0.24773 -0.62172 2.6127
1
data = 236×6 table
ID t Ia If N T __ __________ ______ ________ ________ ______ 10 0 2.6327 -0.24773 -0.62456 2.8281 10 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 10 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 10 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 10 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 10 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 10 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 10 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 10 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 10 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 10 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 10 0.00011391 2.6325 -0.24773 -0.62344 2.6139 10 0.00013051 2.6325 -0.24773 -0.62328 2.6133 10 0.00018404 2.6323 -0.24773 -0.62276 2.6126 10 0.00023757 2.6322 -0.24773 -0.62224 2.6128 10 0.0002911 2.632 -0.24773 -0.62172 2.6127
2
data = 276×6 table
ID t Ia If N T __ __________ ______ ________ ________ ______ 16 0 2.6327 -0.24773 -0.62456 2.8281 16 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 16 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 16 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 16 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 16 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 16 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 16 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 16 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 16 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 16 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 16 0.00011391 2.6325 -0.24773 -0.62344 2.6139 16 0.00013051 2.6325 -0.24773 -0.62328 2.6133 16 0.00018404 2.6323 -0.24773 -0.62276 2.6126 16 0.00023757 2.6322 -0.24773 -0.62224 2.6128 16 0.0002911 2.632 -0.24773 -0.62172 2.6127
3
data = 193×6 table
ID t Ia If N T __ __________ ______ ________ ________ ______ 27 0 2.6327 -0.24773 -0.62456 2.8281 27 4.2188e-06 2.6327 -0.24773 -0.62452 2.7896 27 8.4375e-06 2.6327 -0.24773 -0.62448 2.7579 27 1.2656e-05 2.6327 -0.24773 -0.62443 2.7318 27 2.1367e-05 2.6327 -0.24773 -0.62435 2.6901 27 3.0077e-05 2.6326 -0.24773 -0.62426 2.6624 27 3.8787e-05 2.6326 -0.24773 -0.62417 2.6446 27 4.7497e-05 2.6326 -0.24773 -0.62409 2.6332 27 6.41e-05 2.6326 -0.24773 -0.62393 2.6225 27 8.0703e-05 2.6326 -0.24773 -0.62376 2.6178 27 9.7305e-05 2.6325 -0.24773 -0.6236 2.6153 27 0.00011391 2.6325 -0.24773 -0.62344 2.6139 27 0.00013051 2.6325 -0.24773 -0.62328 2.6133 27 0.00018404 2.6323 -0.24773 -0.62276 2.6126 27 0.00023757 2.6322 -0.24773 -0.62224 2.6128 27 0.0002911 2.632 -0.24773 -0.62172 2.6127
4
data = 116×6 table
ID t Ia If N T __ __________ ______ _______ ________ ______ 43 0 2.6327 -0.2461 -0.62456 2.8296 43 4.2188e-06 2.6327 -0.2461 -0.62452 2.7911 43 8.4375e-06 2.6327 -0.2461 -0.62448 2.7593 43 1.2656e-05 2.6327 -0.2461 -0.62443 2.7333 43 2.1367e-05 2.6327 -0.2461 -0.62435 2.6916 43 3.0077e-05 2.6326 -0.2461 -0.62426 2.6639 43 3.8787e-05 2.6326 -0.2461 -0.62417 2.646 43 4.7497e-05 2.6326 -0.2461 -0.62409 2.6346 43 6.41e-05 2.6326 -0.2461 -0.62393 2.6239 43 8.0703e-05 2.6326 -0.2461 -0.62376 2.6192 43 9.7305e-05 2.6325 -0.2461 -0.6236 2.6167 43 0.00011391 2.6325 -0.2461 -0.62344 2.6153 43 0.00013051 2.6325 -0.2461 -0.62328 2.6147 43 0.00018404 2.6323 -0.2461 -0.62276 2.614 43 0.00023757 2.6322 -0.2461 -0.62224 2.6142 43 0.0002911 2.632 -0.2461 -0.62171 2.6141
5
figure
helperPlotEnsemble(validationdatafused, [], 1, 3)
xlabel('Time')
ylabel('Health Indicator')
title('Validation Data')
Now we do have our training and validation data ready now it is needed to build a ML model to make predictions. We will use residual similarity model which tries to predict the health condition of a machine using 2nd order polynomial. The similarity score is find by formula :
score(i,j)=exp(-d(i,j)^2)
It gives estimate how much two machines are similar.
The code is given below: I have used the 10 nearest neighbours as in tutorial data the train data contains
mdl = residualSimilarityModel(...
'Method', 'poly2',...
'Distance', 'absolute',...
'NumNearestNeighbors', 10,...
'Standardize', 1);
fit(mdl, trainDataFused);
mdl
mdl =
residualSimilarityModel with properties: Models: {38×1 cell} ModelMSE: [38×1 double] LifeSpan: [38×1 double] NumNearestNeighbors: 10 Method: "poly2" Distance: "absolute" IncludeTies: 1 Standardize: 1 LifeTimeVariable: "" LifeTimeUnit: "" DataVariables: "" UserData: [] UseParallel: 0
As the model is fit now to validate we used different amount of validation data i.e.. 50%,70% and 90% which will give much better results for more data. This percentage data we are talking about a single instance like running of machine 50% of its time, 70% of time and we are trying to predict the time for its 100% running condition.
breakpoint = [0.5, 0.7, 0.9];
validationDataTmp = validationdatafused{3};
We have taken only the 3rd validation data profile.
bpidx = 1;
validationDataTmp50 = validationDataTmp(1:ceil(end*breakpoint(bpidx)),:);
trueRUL = length(validationDataTmp) - length(validationDataTmp50);
[estRUL, ciRUL, pdfRUL] = predictRUL(mdl, validationDataTmp50);
figure
compare(mdl, validationDataTmp50);
figure
helperPlotRULDistribution(trueRUL, estRUL, pdfRUL, ciRUL)
bpidx = 2;
validationDataTmp70 = validationDataTmp(1:ceil(end*breakpoint(bpidx)), :);
trueRUL = length(validationDataTmp) - length(validationDataTmp70);
[estRUL,ciRUL,pdfRUL] = predictRUL(mdl, validationDataTmp70);
figure
compare(mdl, validationDataTmp70);
figure
helperPlotRULDistribution(trueRUL, estRUL, pdfRUL, ciRUL)
bpidx = 3;
validationDataTmp90 = validationDataTmp(1:ceil(end*breakpoint(bpidx)), :);
trueRUL = length(validationDataTmp) - length(validationDataTmp90);
[estRUL,ciRUL,pdfRUL] = predictRUL(mdl, validationDataTmp90);
figure
compare(mdl, validationDataTmp90);
figure
helperPlotRULDistribution(trueRUL, estRUL, pdfRUL, ciRUL)
numValidation = length(validationdatafused);
numBreakpoint = length(breakpoint);
error = zeros(numValidation, numBreakpoint);
for dataIdx = 1:numValidation
tmpData = validationdatafused{dataIdx};
for bpidx = 1:numBreakpoint
tmpDataTest = tmpData(1:ceil(end*breakpoint(bpidx)), :);
trueRUL = length(tmpData) - length(tmpDataTest);
[estRUL, ~, ~] = predictRUL(mdl, tmpDataTest);
error(dataIdx, bpidx) = estRUL - trueRUL;
end
end
Now full validation data is used to calculate the error. Just we have repeated the above process used on 3rd entry of validation data on full validation data.
[pdf50, x50] = ksdensity(error(:, 1));
[pdf70, x70] = ksdensity(error(:, 2));
[pdf90, x90] = ksdensity(error(:, 3));
figure
ax(1) = subplot(3,1,1);
hold on
histogram(error(:, 1), 'BinWidth', 5, 'Normalization', 'pdf')
plot(x50, pdf50)
hold off
xlabel('Prediction Error')
title('RUL Prediction Error using first 50% of each validation ensemble member')
ax(2) = subplot(3,1,2);
hold on
histogram(error(:, 2), 'BinWidth', 5, 'Normalization', 'pdf')
plot(x70, pdf70)
hold off
xlabel('Prediction Error')
title('RUL Prediction Error using first 70% of each validation ensemble member')
ax(3) = subplot(3,1,3);
hold on
histogram(error(:, 3), 'BinWidth', 5, 'Normalization', 'pdf')
plot(x90, pdf90)
hold off
xlabel('Prediction Error')
title('RUL Prediction Error using first 90% of each validation ensemble member')
linkaxes(ax)
figure
boxplot(error, 'Labels', {'50%', '70%', '90%'})
ylabel('Prediction Error')
title('Prediction error using different percentages of each validation ensemble member')
errorMean = mean(error)
errorMean = 1×3
-66.8948 -44.9901 4.5332
errorMedian = median(error)
errorMedian = 1×3
-86.7852 -42.5323 -5.7899
errorSD = std(error)
errorSD = 1×3
61.1730 45.6777 25.6444
In our case error is actually 5*3 dimensional, rsn we do have three breaking points we can also increase them but that’s nonsense. Error mean, error standard deviation is found then error bar is plotted, from hypothesis as the amount of data increases the error should decrease. Lets see what happens in the real graph:
figure
errorbar([50 70 90], errorMean, errorSD, '-o', 'MarkerEdgeColor','r')
xlim([40, 100])
xlabel('Percentage of validation data used for RUL prediction')
ylabel('Prediction Error')
legend('Mean Prediction Error with 1 Standard Deviation Eror bar', 'Location', 'south')